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Nemery, De Bellevaux Philippe. "On the use of multicriteria ranking methods in sorting problems." Doctoral thesis, Universite Libre de Bruxelles, 2008. http://hdl.handle.net/2013/ULB-DIPOT:oai:dipot.ulb.ac.be:2013/210424.
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Notre thèse est consacrée à l’étude des méthodes de rangements multicritères dans le cadre de la problématique de tri.
Dans un problème de tri une personne, appelée décideur, désire assigner un objet, appelé action, à des catégories prédéfinies. Des problèmes de tri surgissent régulièrement dans la vie de tous les jours. Par exemple, un médecin ausculte son patient et sur base des symptômes observés, il assigne son patient à une catégorie de pathologies. Ainsi, le médecin peut prescrire un traitement approprié. Par ailleurs, on catégorise les cyclones tropicaux en fonction de leur vitesse, pression superficielle et de la hauteur de marée. En fonction de la catégorie du cyclone, des dégâts éventuels peuvent être prédits et des mesures de protection adéquates devront être prises.
Dans un problème de tri, un décideur regroupe ainsi les actions qu’il considère similaires, à des fins descriptives, organisationnelles ou préventives. Nous supposerons en outre que le décideur exprime une relation de préférence entre les classes préalablement définies.
D’autre part, les méthodes de rangement permettent de ranger les actions de la meilleure à la moins bonne. Nul étudiant ne peut nier l’existence des " rankings " d’universités. Une société ordonne les candidats à l’issue d’un entretien d’embauche. Une société désire par ailleurs établir des partenariats avec les fournisseurs les plus performants. Nous sommes tous confrontés à cette tâche délicate de ranger les actions de la meilleure à la moins bonne. Les méthodes d’aide à la décision proposent des techniques permettant à un décideur d’obtenir un rangement d’actions.
L’objectif de cette thèse est d’étudier la possibilité de résoudre des problèmes de tri à l’aide de méthodes de rangement. L’approche adoptée est de ranger une action particulière par rapport à des normes ou profils définissant les catégories. L’assignation de l’action sera dès lors basée sur sa position dans ce rangement particulier.
Quelles sont les hypothèses nécessaires pour un tel modèle ?Ces méthodes présentent-elles un biais ou ont-elles d’autres avantages par rapport aux méthodes de tri existantes? Est-il préférable de modéliser les catégories à l’aide de critères même si celles-ci ne présentent pas de relation de préférence ?Dans cette thèse nous donnerons des premiers éléments de réponse en développant de nouvelles méthodes de tri basées sur des méthodes de rangement existantes.
Doctorat en Sciences de l'ingénieur
info:eu-repo/semantics/nonPublished
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Tufekci, Nesrin. "Gis Based Geothermal Potential Assessment For Western Anatolia." Master's thesis, METU, 2006. http://etd.lib.metu.edu.tr/upload/12607651/index.pdf.
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This thesis aims to predict the probable undiscovered geothermal systems through investigation of spatial relation between geothermal occurrences and its surrounding geological phenomenon in Western Anatolia. In this context, four different public data, which are epicenter map, lineament map, Bouger gravity anomaly and magnetic anomaly maps, are utilized. In order to extract the necessary information for each map layer the raw public data is converted to a synthetic data which are directly used in the analysis. Synthetic data employed during the investigation process include Gutenberg-Richter b-value map, distance to lineaments map and distance to major grabens present in the area. Thus, these three layers including directly used magnetic anomaly maps are combined by means of Boolean logic model and Weights of Evidence method (WofE), which are multicriteria decision methods, in a Geographical Information System (GIS) environment. Boolean logic model is based on the simple logic of Boolean operators, while the WofE model depends on the Bayesian probability. Both of the methods use binary maps for their analysis. Thus, the binary map classification is the key point of the analysis. In this study three different binary map classification techniques are applied and thus three output maps were obtained for each of the method. The all resultant maps are evaluated within and among the methods by means of success indices. The findings reveal that the WofE method is better predictor than the Boolean logic model and that the third binarization approach, which is named as optimization procedure in this study, is the best estimator of binary classes due to obtained success indices. Finally, three output maps of each method are combined and the favorable areas in terms of geothermal potential are produced. According to the final maps the potential sites appear to be Aydin, Denizli and Manisa, of which first two have been greatly explored and exploited since today and thus not surprisingly found as potential in the output maps, while Manisa when compared to first two is nearly virgin.
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Загородня, Тетяна Миколаївна. "Моделі та інформаційна технологія забезпечення компетентності випускників вищого навчального закладу з урахуванням вимог роботодавця." Thesis, Сумський державний університет, 2015. http://repository.kpi.kharkov.ua/handle/KhPI-Press/18188.
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Дисертація на здобуття наукового ступеня кандидата технічних наук за спеціальністю 05.13.06 – інформаційні технології. – Національний технічний університет "Харківський політехнічний інститут", Харків, 2015. У дисертаційній роботі вирішена актуальна науково-практична задача обґрунтування та розробки інформаційної технології забезпечення компетентності випускників ВНЗ з урахуванням вимог роботодавця до компетентності фахівців. Проаналізовано наукові досягнення в області підвищення ефективності навчання з урахуванням модульної системи і компетентісного підходу, сформульовано основні вимоги до інформаційної системи підтримки прийняття рішень для викладацького складу з метою вдосконалення процесу навчання студентів технічних спеціальностей, зокрема, майбутніх інженерів. Створено математичну модель представлення компетентності студентів як складної агрегованої характеристики. Розроблено модель багатокритеріальної оптимізації параметрів навчального процесу, яка дозволяє максимізувати функцію компетентності. Розроблено і впроваджено відповідну інформаційну технологію підтримки прийняття рішень, яка дозволяє проводити оптимізацію процесу навчання студентів технічних спеціальностей задля підвищення їхньої компетентності, що відповідає вимогам роботодавців. Здійснено оптимізацію параметрів навчального процесу для студентів заочної форми навчання, які вивчають дисципліну "Теоретичні основи електротехніки", що дозволяє підвищити сформований рівень компетентності на 20-35 %. Результати впроваджено та використано під час організації навчального процесу у провідних закладах вищої освіти України.
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Загородня, Тетяна Миколаївна. "Моделі та інформаційна технологія забезпечення компетентності випускників вищого навчального закладу з урахуванням вимог роботодавця." Thesis, НТУ "ХПІ", 2015. http://repository.kpi.kharkov.ua/handle/KhPI-Press/18178.
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Дисертація на здобуття наукового ступеня кандидата технічних наук за спеціальністю 05.13.06 – інформаційні технології. – Національний технічний університет "Харківський політехнічний інститут", Харків, 2015.
У дисертаційній роботі вирішена актуальна науково-практична задача обґрунтування та розробки інформаційної технології забезпечення компетентності випускників ВНЗ з урахуванням вимог роботодавця до компетентності фахівців. Проаналізовано наукові досягнення в області підвищення ефективності навчання з урахуванням модульної системи і компетентісного підходу, сформульовано основні вимоги до інформаційної системи підтримки прийняття рішень для викладацького складу з метою вдосконалення процесу навчання студентів технічних спеціальностей, зокрема, майбутніх інженерів. Створено математичну модель представлення компетентності студентів як складної агрегованої характеристики. Розроблено модель багатокритеріальної оптимізації параметрів навчального процесу, яка дозволяє максимізувати функцію компетентності. Розроблено і впроваджено відповідну інформаційну технологію підтримки прийняття рішень, яка дозволяє проводити оптимізацію процесу навчання студентів технічних спеціальностей задля підвищення їхньої компетентності, що відповідає вимогам роботодавців. Здійснено оптимізацію параметрів навчального процесу для студентів заочної форми навчання, які вивчають дисципліну "Теоретичні основи електротехніки", що дозволяє підвищити сформований рівень компетентності на 20-35 %. Результати впроваджено та використано під час організації навчального процесу у провідних закладах вищої освіти України.Thesis for a Candidate Degree in Technical Sciences, Specialty 05.13.06 – Information technologies. – National Technical University "Kharkiv Polytechnic Institute", Kharkiv, 2015. In the dissertation the relevant scientific and practical problem is solved, which is related to study and development of information technology for ensuring competencies of graduates to meet the requirements of the employer for the competence of professionals. Scientific achievements in the field of improving of learning efficiency based on a modular system and the competence approach were analyzed. The basic requirements to decision support information system for teaching staff were formulated in order to improve the learning process of students of technical specialties, including future engineers. A mathematical model of competence representation as a complex aggregated characteristic was created. The model of multicriteria optimization of the parameters of learning process was developed, which allows to maximize the competence function. The decision support information technology was developed and deployed. It allows to optimize the learning process of students of technical specialties for improvement of their competence and satisfaction of employers requirements. The optimization of parameters of learning process for students of low residence education was performed. It was done for discipline «Theoretical Foundations of Electrical Engineering» and allowed to increase the level of competence by 20–35 %. The results were used for organization of learning process in leading universities of Ukraine.
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Vafaeyan, Shadi. "A new approach to the Rough Set multicriteria optimisation method." Thesis, University of Ottawa (Canada), 2007. http://hdl.handle.net/10393/28031.
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In the recent years, enormous amount of attention has been given to multicriteria optimisation problems. These are problems with conflicting objectives, to which it is impossible to obtain an optimum solution that contains the best value for every criterion simultaneously, therefore the decision maker must decide on a reasonable compromise. There have been numerous developments of optimisation methods to aid the decision-maker in addressing such problems. These methods can be divided to two categories based on the use or not of the Pareto domain (PD). The Pareto domain is the set of all non-dominated solutions to the multicriteria problem, where no solution is better or worse than any other in the set when all the criteria are considered equal in importance.
This thesis is a collection of two papers that focuses on a new approach to the Rough Set multicriteria optimisation technique. Rough Set method (RSM) requires the determination of the PD as the first step to the optimisation process. In the suggested new approach to RSM, a more systematic way in the selection of points from the PD, that is given to the expert for ranking and then the generation of rules by which the entire PD is ranked, is presented. The RSM that operates based on this new approach was applied to three case studies in paper 1 and to "Beer quality optimisation" in the second paper. The results were compared to the ones obtained by the traditional RSM, Net Flow method and the simple Least Squares method. In conclusion, the new RSM showed to be the most reliable and robust method of all.
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Buonanno, Michael Alexander. "A Method for Aircraft Concept Exploration using Multicriteria Interactive Genetic Algorithms." Diss., Georgia Institute of Technology, 2005. http://hdl.handle.net/1853/7571.
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The problem of aircraft concept selection has become increasingly difficult in recent years due to changes in the primary evaluation criteria of concepts. In the past, performance was often the primary discriminator whereas modern programs have placed increased emphasis on factors such as environmental impact, economics, supportability, aesthetics, and other metrics. The revolutionary nature of the vehicles required to simultaneously meet these conflicting requirements has prompted a shift from design using historical data regression techniques for metric prediction to the use of sophisticated physics-based analysis tools that are capable of analyzing designs outside of the historical database. The use of optimization methods with these physics-based tools, however, has proven difficult because of the tendency of optimizers to exploit assumptions present in the models and drive the design towards a solution which, while promising to the computer, may be infeasible due to factors not considered by the computer codes. In addition to this difficulty, the number of discrete options available at this stage may be unmanageable due to the combinatorial nature of the concept selection problem, leading the analyst to select a sub-optimum baseline vehicle. Some extremely important concept decisions, such as the type of control surface arrangement to use, are frequently made without sufficient understanding of their impact on the important system metrics due to a lack of historical guidance, computational resources, or analysis tools.
This thesis discusses the difficulties associated with revolutionary system design, and introduces several new techniques designed to remedy them. First, an interactive design method has been developed that allows the designer to provide feedback to a numerical optimization algorithm during runtime, thereby preventing the optimizer from exploiting weaknesses in the analytical model. This method can be used to account for subjective criteria, or as a crude measure of un-modeled quantitative criteria. Other contributions of the work include a modified Structured Genetic Algorithm that enables the efficient search of large combinatorial design hierarchies and an improved multi-objective optimization procedure that can effectively optimize several objectives simultaneously. A new conceptual design method has been created by drawing upon each of these new capabilities and aspects of more traditional design methods.
The ability of this new technique to assist in the design of revolutionary vehicles has been demonstrated using a problem of contemporary interest: the concept exploration of a supersonic business jet. This problem was found to be a good demonstration case because of its novelty and unique requirements, and the results of this proof of concept exercise indicate that the new method is effective at providing additional insight into the relationship between a vehicle's requirements and its favorable attributes.
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PAIXÃO, GIOVANNA PATE DA. "STOCK PORTFOLIO SELECTION MODEL: AN APPLICATION OF MULTICRITERIA METHOD ANALYTIC HIERARCHY PROCESS." PONTIFÍCIA UNIVERSIDADE CATÓLICA DO RIO DE JANEIRO, 2013. http://www.maxwell.vrac.puc-rio.br/Busca_etds.php?strSecao=resultado&nrSeq=34578@1.
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Com o intuito de obter parte do lucro futuro de uma empresa, o investidor adquire uma ação - título que representa a menor parcela do capital de uma empresa. Tal investidor, interessado em investir em ações, se depara com uma primeira decisão a tomar: em quais ações investir. Existem diversos métodos para a seleção de ações, podendo ser classificados em métodos puramente objetivos, puramente subjetivos e métodos compostos. O presente trabalho visa propor um método composto, baseado no modelo multicritério Analytic Hierarchy Process (AHP), para ordenar as ações nas quais o investidor deve investir dado um determinado grupo de ações pré-selecionado. Com base no presente estudo, o modelo proposto demonstrou ser uma ferramenta de simples aplicação e viável para que qualquer investidor – dos mais qualificados aos menos qualificados – possa tomar a decisão de escolha de ações utilizando esta ferramenta. Dentre a amostra de 10 ações pré selecionadas, as empresas que obtiveram maior pontuação, e por isso, fariam parte do portfólio de ações, foram: Itaú Unibanco, BMF Bovespa e Vale.In order to obtain a part of the future profit of a company, an investor buys a stock - the smaller share of a company s capital. The investor, interested in putting money into stocks, faces his/her first decision: in which stock to invest. There are several methods to select the stocks which can be classified as purely objective method, purely subjective and combined method. This paper intends to propose a combined method based on the multicriteria model Analytic Hierarchy Process (AHP) in order to rank stocks for investors to choose his/her investments from the given group of stocks. Based on this study, the proposed model proved to be a simple application tool and viable for any investor - from the most qualified to least qualified - be able to make decision of choosing stocks using this tool. Among the sample of 10 pre selected stocks, the ones which achieved a higher score, and therefore would be part of the portfolio of shares, were: Itaú Unibanco and Vale BMF Bovespa.
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Dur, Fatih Çelik H. Murat. "The Usage Of Stochastic And Multicriteria Decision-Aid Methods Evaluating Geothermal Energy Exploitation Projects/." [s.l.]: [s.n.], 2005. http://library.iyte.edu.tr/tezler/master/sehirplanlama/T000324.pdf.
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Thesis (Master)--İzmir Institute of Technology, İzmir, 2005.Keywords: Geothermal energy, multi criteria decision method, stochastic methods, Monte Carlo method. Includes bibliographical references (leaves.93-98).
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GOMES, KESIA GUEDES ARRAES. "A MULTICRITERIA METHOD FOR THE LOCATION OF INTENDANCY CELLULAR UNITS OF THE BRAZILIAN AIR FORCE." PONTIFÍCIA UNIVERSIDADE CATÓLICA DO RIO DE JANEIRO, 2009. http://www.maxwell.vrac.puc-rio.br/Busca_etds.php?strSecao=resultado&nrSeq=14984@1.
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As Unidades Celulares de Intendência (UCI) da Força Aérea Brasileira são
estruturas móveis destinadas a prestar o apoio logístico ao homem, quando deslocado
de sua Organização Militar de origem, para cumprir missão real ou de adestramento,
em locais remotos ou desprovidos de recursos. Na FAB, existem oito UCI
distribuídas regionalmente pelo território nacional brasileiro. Para atender ao Plano de
Articulação da FAB e aos ditames da Estratégia Nacional de Defesa, vários estudos
foram desenvolvidos, na Diretoria de Intendência, Órgão Central do Sistema de
Intendência Operacional, acerca da sistemática de distribuição (localização) dessas
Unidades para melhor atender às exigências operacionais da Força. Com o intuito de
permitir uma maior compreensão sobre o tema, esta dissertação apresenta a aplicação
de um método multicritério de apoio à decisão, denominado AHP (Analytic
Hierarchy Process), com vistas a facilitar o processo de escolha e priorização da
localização estratégica das UCI da FAB, contemplando o possível fechamento de três
Unidades Celulares de Intendência. O método AHP, desenvolvido por Thomas L.
Saaty, permite a estruturação hierárquica de um problema estratégico complexo, a
incorporação das preferências dos decisores na mensuração dos fatores qualitativos
envolvidos, bem como a aplicação de uma abordagem que pode agregar variáveis
intangíveis monetariamente. A relevância do tema permitiu a participação de Oficiais
da Diretoria de Intendência que são experientes e peritos no assunto, facilitando a
captação das informações e dos dados necessários à aplicação do método.The Intendancy Cellular Units (UCI) of the Brazilian Air Force are mobile structures which aim at providing the logistic support to man, when he’s displaced from his Military Organization in order to accomplish real or training missions in remote areas or places that lack resources. In the Brazilian Air Force, there are eight UCI which are regionally distributed along the Brazilian national territory. Considering the need to fulfill the Brazilian Air Force Articulation Plan and the National Defense Strategy, many studies were developed in the Directory of Intendancy, Main Body that is responsible for the Operational Intendancy System, to evaluate the distribution (location) of these Units so as to comply with the operational demands of the Air Force. With the need to better understand the subject, this research presents the application of a multi-criteria decision making method, namely AHP (Analytic Hierarchy Process), to facilitate the process of choosing and prioritizing the UCI strategic location, taking into consideration the possible closure of three Intendancy Cellular Units. The AHP method, developed by Thomas L. Saaty, allows for the hierarchical structure of a complex strategic problem, the incorporation of decision makers preferences when measuring all the qualitative aspects involved as well as the use of an approach that can aggregate monetary intangible variables. Given the theme’s relevance, the participation of wise and expert Officers from the Directory of Intendancy enabled the perception of information and the necessary data in order to apply the method.
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Dannert, Sofia, and Josefin Norström. "Metod för bedömning och jämförelse av insamlings- och sorteringssystem för hushållsavfall : Utveckling av ett verktyg för multikriterieanalys med en- och fåfamiljshus i Linköpings kommun som fall." Thesis, Linköpings universitet, Industriell miljöteknik, 2018. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-148883.
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En av de största globala utmaningarna idag är de negativa miljöeffekterna från den linjära ekonomin som världen bygger på, där produkter oupphörligt skapas från jungfruliga råvaror och efter användningstiden slutar som avfall utan nytta. Initiativ på flera nivåer; lokalt, regionalt, nationellt och globalt, krävs för att uppnå en cirkulär ekonomi där uppkomsten av avfall, samt utvinningen av jungfruliga råvaror, minskar. Europeiska unionens handlingsplan för cirkulär ekonomi säger att 75 % av alla förpackningar ska materialåtervinnas till år 2030. I Sverige materialåtervinns mellan 42,2 % (plastförpackningar) och 95 % (glas) och fastighetsnära insamlingssystem för förpackningar och tidningar är förhållandevis väl utbyggda, åtminstone för flerfamiljshus. Gällande småhus har utvecklingen gått något långsammare även om flera kommuner idag infört fastighetsnära insamling för hushållsavfall, inklusive förpacknings- och tidningsavfall. Att välja ett nytt, utökat avfallssystem till en kommun är ett stort och komplext beslut med många aspekter att ta hänsyn till. Flera tidigare utredningar inför denna typ av beslut har saknat en tydlig målbild, metodik och systematik i granskningen, varför syftet med denna studie varit att utveckla en metod för att genomföra en systematisk multikriterieanalys av ett antal avfallssystem för insamling och sortering av hushållsavfall från småhus i en kommun. Innan multikriterieanalysen påbörjades gjordes en omfattande kartläggning av de aspekter som är kopplade till beslutet om ett nytt avfallssystem. Kartläggningen och det urval av aspekter som gjordes till multikriterieanalysen är värdefull kunskap för kommuner som står inför denna typ av beslut. Multikriterieanalysen har tagits fram med inspiration från den generiska formen av en multikriterieanalys där Linköpings kommun och Tekniska verken använts som fall. På grund av detta har även de system som utvärderats valts ut med hänsyn till intressanta avfallssystem för Linköpings kommun. Den framtagna multikriterieanalysen har paketerats i ett användarvänligt verktyg som kan användas av beslutsfattare i kommuner som önskar att utvärdera och jämföra avfallssystem för småhus. Studien har resulterat i att det i huvudsak är följande sju kriterier som bör beaktas i en utredning gällande ett nytt insamlings- och sorteringssystem för småhus i en kommun, där resurseffektivitet är av hög prioritet i beslutet: One of the greatest challenges the world is facing today is the negative environmental effects as a result from the linear economy used in societies, where products are constantly being produced from raw materials and end up as waste after the period of usage. Initiatives on many levels; local, regional, national and global are needed to create a circular economy which minimizes both the generation of waste and the extraction of raw materials. The European Union’s action plan for circular economy expresses that 75 % of all packaging waste should be recycled by 2030. In Sweden packaging waste is being recycled between 42,2 % (plastic waste) to 95 % (glass waste) and the curbside collection systems for packaging waste are quite well-developed, especially regarding waste systems for multi-family houses. For single-family houses the development has been slower, although several municipalities have introduced curbside collection systems for household waste including packaging and newspaper waste during the last years. It is a comprehensive and complex decision to invest in a new extended curbside collection and sorting system in a municipality and there are many aspects to consider. Since several previous inquiries regarding this type of decision lacks a systematic approach and clear objectives, the purpose of this study is to develop a method for conducting a systematic multi-criteria analysis of collection and sorting systems for single-family household waste in a municipality. Prior to the multi-criteria analysis a substantial evaluation of aspects related to the decision of a new waste system was made. The mapping and selection of aspects that were made provide great knowledge for municipalities facing this kind of decision. The developed multi-criteria analysis is based on the generic form of a multi-criteria analysis, using the municipality of Linköping and Tekniska verken as case. As a result, the range of waste systems evaluated have been selected according to the preferences of Linköping municipality. The developed multi-criteria analysis has been transferred to a user-friendly tool for decision makers at municipalities who wish to assess and compare extended collection and sorting systems for single-family household waste. The study has resulted in the following criteria which should be considered in an inquiry of waste systems for single-family houses in a municipality, where resource efficiency is highly prioritized:
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Maskeliūnaitė, Lijana. "The model for multicriteria evaluation of the quality of passenger transportation by international trains." Doctoral thesis, Lithuanian Academic Libraries Network (LABT), 2013. http://vddb.laba.lt/obj/LT-eLABa-0001:E.02~2013~D_20130122_170551-82864.
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The dissertation considers the problems, associated with passenger transportation by international trains (PTIT). The research object is the process of passenger transportation by international trains (PPTIT). By using the experimental methods, the significances (weights) and the order of preferences of the qualitative criteria, describing this process, are determined. The complex model, deve-loped by the author for multicriteria PTIT evaluation, allows for determining a single-valued quantitative criterion for evaluating a particular train travelling on a particular route. The main aim of the dissertation is to offer a methodology for evaluating the quality of passenger transportation by international trains (QPTIT).
The dissertation consists of the Introduction, four chapters, the description of the obtained results, the list of references as well as the author’s publications on the topic of the thesis and 12 annexes.
The Introduction briefly describes the research problem and object, the topicality of the work, its aim and objectives, and the applied research methods, as well as the novelty and practical value of the results obtained and the defended statements. Finally, the Introduction presents the list of the author’s publications and reports delivered at the conferences on the topic of the dissertation.
Chapter 1 presents the analysis of the Lithuanian and EU standards and regulations, defining the quality of passenger transportation by rail. It also describes the... [to full text]Disertacijoje nagrinėjamos tarptautinio keleivių vežimo geležinkeliais (TKVG) problemos. Pagrindinis darbo objektas – tarptautinio keleivių vežimo geležinkeliais procesas (TKVGP). Eksperimentiniais metodais nustatyti kelionės traukiniu kokybės kriterijų reikšmingumas ir šių kriterijų grupių svarba (pirmumas). Autorės suformuluotas TKVG kompleksinis daugiakriterinis vertinimo modelis leido nustatyti vieno traukinio, vykstančio tam tikru maršrutu, vienareikšmį kiekybinį rodiklį. Pagrindinis disertacijos tikslas – pateikti tarptautinio keleivių vežimo geležinkeliais (kelionės traukiniu) kokybės (TKVGK) vertinimo metodologiją. Disertaciją sudaro įvadas, keturi skyriai, rezultatų apibendrinimas, naudotos literatūros ir autorės publikacijų disertacijos tema sąrašai bei 12 priedų. Įvade trumpai aptarta tiriamoji problema, darbo aktualumas, pristatytas tyrimų objektas, suformuluotas darbo tikslas bei uždaviniai, aprašyta tyrimų metodika, mokslinis darbo naujumas, praktinė rezultatų reikšmė bei pateikti ginamieji teiginiai. Įvado pabaigoje pristatomos autorės paskelbtos publikacijos ir pranešimai konferencijose disertacijos tema. Pirmajame skyriuje atlikta geležinkelio infrastruktūros, riedmenų ir TKVGP mokslinių darbų analizė. Taip pat atlikta Lietuvos Respublikos (Europos Sąjungos) norminių dokumentų, reglamentuojančių keleivių vežimo geležinkeliais kokybę, analizė. Antrasis skyrius skirtas AB ,,Lietuvos geležinkeliai“ (LG) veiklos ir keleivių vežimo rodiklių apžvalgai, kelionės... [toliau žr. visą tekstą]
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FranÃa, Francisco Mavignier Cavalcante. "Indicators integrated sustainability and analysis multicriteria dams underground in Cearà state." Universidade Federal do CearÃ, 2016. http://www.teses.ufc.br/tde_busca/arquivo.php?codArquivo=17258.
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Instituto Centro de Ensino TecnolÃgicoThe underground dam is a social technology of low cost and simple process of construction and operation. In the semi-arid zone of Ceara there is potential to build approximately 3,400 underground dams. The central problem of this study is the lack of in-depth knowledge of the degree of sustainability of underground dams of CearÃ, in economic, social, environmental and institutional terms. The objective of this thesis is to analyze the sustainability of underground dams, the state of CearÃ, as a social technology to living as semi-arid. For this, we used the Dashboard of Sustainability Method by dimension and global, and the Analytic Hierarchy Process to identify the underground dam operating alternative that generates greater benefits to communities. The questionnaires (field research), for the use of Dashboard of Sustainability method, was carried out with 40 farmers, owners of underground dams, located in 11 municipalities of the State of CearÃ. The collection of judgments, for the application of Analytic Hierarchy Process applied together 11 experts and / or decision-makers with expertise in underground dams. When using the Dashboard of Sustainability method, which aims to identify the level of performance of sustainable development for indicator by size and global, were selected with the help of principal component analysis, 28 indicators. These indicators, only 36% achieved the level of 700 points, which is the sustainability threshold used in this thesis. None of the four dimensions reached the level of 700 points. The lower performance was with the economic dimension, reaching only 218 points (need for severe attention) when the maximum metric desirable for the model is 1,000 points or at least the threshold of sustainability of 700 points. The overall index, sustainable development (IGDS) of underground dams of Ceara, reached the metric of 538 points, considered an average level of performance and below the sustainability threshold. The selection of dam alternatives, made by AHP, according to the predominant use, showed that the highest priority for investment, to be decided by the public manager is to "underground dam focused on water supply," closely followed by "underground dam focused on agricultural production". The lowest metric was to "dam focused on environmental benefits", with a metric that reached only 33% of the first alternative. Another important finding that deserves reflection, was that farmers (ex-post analysis) have recorded reasonable performance of the environmental dimension indicators, while the expert and decision-makers (analysis ex-ante) have rated the "dam focused on earnings environmental" the third priority, with metric equal to one third of the first alternative.
A barragem subterrÃnea à uma tecnologia social de baixo custo e de processo simples de construÃÃo e operaÃÃo. Na zona semiÃrida do Estado do Cearà hà potencial para construÃÃo de, aproximadamente, 3.400 barragens subterrÃneas. O problema central, deste estudo, à a falta de conhecimento aprofundado do grau de sustentabilidade das barragens subterrÃneas do CearÃ, em termos econÃmicos, sociais, ambientais e institucionais. Assim, o objetivo desta tese à analisar a sustentabilidade das barragens subterrÃneas, do Estado do CearÃ, como uma tecnologia social para convivÃncia como semiÃrido. Para isto, utilizou-se o mÃtodo Painel de Sustentabilidade (Dashboard of Sustainability), por dimensÃo e global, e o MÃtodo de AnÃlise HierÃrquica (Analytic Hierarchy Process) para identificar a alternativa de exploraÃÃo de barragem subterrÃnea que gera maiores benefÃcios Ãs comunidades. A aplicaÃÃo dos questionÃrios (pesquisa de campo), para a utilizaÃÃo do mÃtodo Painel de Sustentabilidade, foi realizada junto a 40 agricultores, proprietÃrios das barragens subterrÃneas, localizados em 11 municÃpios do Estado do CearÃ. A coleta dos julgamentos, para a aplicaÃÃo do MÃtodo de AnÃlise HierÃrquica, aplicada junto a 11 especialistas e/ou decisores, com experiÃncia em barragens subterrÃneas. Na utilizaÃÃo do Painel de Sustentabilidade, que visa identificar o grau de desempenho de indicadores de desenvolvimento sustentÃvel por indicador, por dimensÃo e global, foram selecionados com o auxÃlio da anÃlise de componentes principais, 28 indicadores. Destes indicadores, apenas 36% alcanÃaram o patamar de 700 pontos, que à o limiar da sustentabilidade adotado nesta tese. Nenhuma das quatro dimensÃes atingiu o patamar de 700 pontos. O mais baixo desempenho ficou com a dimensÃo econÃmica, ao atingir apenas 218 pontos (necessidade de atenÃÃo severa), quando a mÃtrica mÃxima desejÃvel para o modelo à 1.000 pontos ou, no mÃnimo, o limiar da sustentabilidade de 700 pontos. O Ãndice global, de desenvolvimento sustentÃvel (IGDS) das barragens subterrÃneas do Estado do CearÃ, atingiu a mÃtrica de 538 pontos, considerado um grau mÃdio de desempenho e abaixo do limiar da sustentabilidade. A seleÃÃo das alternativas de barragens, feita pelo MÃtodo AHP, segundo o uso predominante, mostrou que a maior prioridade para investimento, a ser decidida pelo gestor pÃblico, à para a âbarragem subterrÃnea focada na oferta de Ãguaâ, seguida de perto pela âbarragem subterrÃnea focada na produÃÃo agrÃcolaâ. A menor mÃtrica ficou para a âbarragem focada em ganhos ambientaisâ, com uma mÃtrica que alcanÃou apenas 33% da primeira alternativa. Outra constataÃÃo relevante, que merece reflexÃo, foi o fato de os agricultores (anÃlise ex-post) terem registrado um razoÃvel desempenho dos indicadores da dimensÃo ambiental, enquanto os especialista e decisores (anÃlise ex-ante) terem classificado a âbarragem focada em ganhos ambientaisâ na terceira prioridade, com mÃtrica igual a um terÃo da primeira alternativa.
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França, Francisco Mavignier Cavalcante. "Indicators integrated sustainability and analysis multicriteria dams underground in Ceará state." reponame:Repositório Institucional da UFC, 2016. http://www.repositorio.ufc.br/handle/riufc/19077.
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FRANÇA, Francisco Mavignier Cavalcante. Indicators integrated sustainability and analysis multicriteria dams underground in Ceará state. 2016. 166 f. : Tese (doutorado) - Universidade Federal do Ceará, Pró-Reitoria de Pesquisa e Pós-graduação, Programa de Pós-Graduação em Desenvolvimento e Meio Ambiente, Fortaleza-CE, 2016Submitted by Nádja Goes (nmoraissoares@gmail.com) on 2016-08-12T14:47:24Z No. of bitstreams: 1 2016_tese_fmcfrança.pdf: 3776458 bytes, checksum: 7051da08a8b5dd0421f041da65f8f3f7 (MD5)
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The underground dam is a social technology of low cost and simple process of construction and operation. In the semi-arid zone of Ceara there is potential to build approximately 3,400 underground dams. The central problem of this study is the lack of in-depth knowledge of the degree of sustainability of underground dams of Ceará, in economic, social, environmental and institutional terms. The objective of this thesis is to analyze the sustainability of underground dams, the state of Ceará, as a social technology to living as semi-arid. For this, we used the Dashboard of Sustainability Method by dimension and global, and the Analytic Hierarchy Process to identify the underground dam operating alternative that generates greater benefits to communities. The questionnaires (field research), for the use of Dashboard of Sustainability method, was carried out with 40 farmers, owners of underground dams, located in 11 municipalities of the State of Ceará. The collection of judgments, for the application of Analytic Hierarchy Process applied together 11 experts and / or decision-makers with expertise in underground dams. When using the Dashboard of Sustainability method, which aims to identify the level of performance of sustainable development for indicator by size and global, were selected with the help of principal component analysis, 28 indicators. These indicators, only 36% achieved the level of 700 points, which is the sustainability threshold used in this thesis. None of the four dimensions reached the level of 700 points. The lower performance was with the economic dimension, reaching only 218 points (need for severe attention) when the maximum metric desirable for the model is 1,000 points or at least the threshold of sustainability of 700 points. The overall index, sustainable development (IGDS) of underground dams of Ceara, reached the metric of 538 points, considered an average level of performance and below the sustainability threshold. The selection of dam alternatives, made by AHP, according to the predominant use, showed that the highest priority for investment, to be decided by the public manager is to "underground dam focused on water supply," closely followed by "underground dam focused on agricultural production". The lowest metric was to "dam focused on environmental benefits", with a metric that reached only 33% of the first alternative. Another important finding that deserves reflection, was that farmers (ex-post analysis) have recorded reasonable performance of the environmental dimension indicators, while the expert and decision-makers (analysis ex-ante) have rated the "dam focused on earnings environmental" the third priority, with metric equal to one third of the first alternative.
A barragem subterrânea é uma tecnologia social de baixo custo e de processo simples de construção e operação. Na zona semiárida do Estado do Ceará há potencial para construção de, aproximadamente, 3.400 barragens subterrâneas. O problema central, deste estudo, é a falta de conhecimento aprofundado do grau de sustentabilidade das barragens subterrâneas do Ceará, em termos econômicos, sociais, ambientais e institucionais. Assim, o objetivo desta tese é analisar a sustentabilidade das barragens subterrâneas, do Estado do Ceará, como uma tecnologia social para convivência como semiárido. Para isto, utilizou-se o método Painel de Sustentabilidade (Dashboard of Sustainability), por dimensão e global, e o Método de Análise Hierárquica (Analytic Hierarchy Process) para identificar a alternativa de exploração de barragem subterrânea que gera maiores benefícios às comunidades. A aplicação dos questionários (pesquisa de campo), para a utilização do método Painel de Sustentabilidade, foi realizada junto a 40 agricultores, proprietários das barragens subterrâneas, localizados em 11 municípios do Estado do Ceará. A coleta dos julgamentos, para a aplicação do Método de Análise Hierárquica, aplicada junto a 11 especialistas e/ou decisores, com experiência em barragens subterrâneas. Na utilização do Painel de Sustentabilidade, que visa identificar o grau de desempenho de indicadores de desenvolvimento sustentável por indicador, por dimensão e global, foram selecionados com o auxílio da análise de componentes principais, 28 indicadores. Destes indicadores, apenas 36% alcançaram o patamar de 700 pontos, que é o limiar da sustentabilidade adotado nesta tese. Nenhuma das quatro dimensões atingiu o patamar de 700 pontos. O mais baixo desempenho ficou com a dimensão econômica, ao atingir apenas 218 pontos (necessidade de atenção severa), quando a métrica máxima desejável para o modelo é 1.000 pontos ou, no mínimo, o limiar da sustentabilidade de 700 pontos. O índice global, de desenvolvimento sustentável (IGDS) das barragens subterrâneas do Estado do Ceará, atingiu a métrica de 538 pontos, considerado um grau médio de desempenho e abaixo do limiar da sustentabilidade. A seleção das alternativas de barragens, feita pelo Método AHP, segundo o uso predominante, mostrou que a maior prioridade para investimento, a ser decidida pelo gestor público, é para a “barragem subterrânea focada na oferta de água”, seguida de perto pela “barragem subterrânea focada na produção agrícola”. A menor métrica ficou para a “barragem focada em ganhos ambientais”, com uma métrica que alcançou apenas 33% da primeira alternativa. Outra constatação relevante, que merece reflexão, foi o fato de os agricultores (análise ex-post) terem registrado um razoável desempenho dos indicadores da dimensão ambiental, enquanto os especialista e decisores (análise ex-ante) terem classificado a “barragem focada em ganhos ambientais” na terceira prioridade, com métrica igual a um terço da primeira alternativa.
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De, Lance Holmes Christopher Charles. "Bayesian method for nonlinear classification and regression." Thesis, Imperial College London, 2001. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.394926.
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Vega, Irizarry Alfredo. "Average likelihood method for classification of CDMA." Thesis, State University of New York at Buffalo, 2016. http://pqdtopen.proquest.com/#viewpdf?dispub=10127689.
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Signal classification or automatic modulation classification is an area of research that has been studied for many years, originally motivated by military applications and in current years motivated by the development of cognitive radios. Its functions may include the surveillance of signals of interest and providing information to blind demodulation systems.
The problem of classifying Code Division Multiple Access (CDMA) signals in the presence of Additive White Gaussian Noise (AGWN) is explored using Decision Theory. Prior state-of-the-art has been limited to single channel digital signals such as MPSK and QAM, with few limited attempts to develop a CDMA classifiers. Such classifiers make use of the cyclic correlation spectrum for single user and feature-based neural network approach for multiple user CDMA. Other approaches have focused on blind detection, which could be used for classification in an indirect manner.
The discussion is focused on the development of classifiers using the average likelihood function. This approach will ensure that the development is optimal in the sense of minimizing the error in classification when compared with any other types of classification techniques. However, this approach has a challenging problem: it requires averaging over many unknown parameters and can become an intractable problem.
This research was successful in reducing some of the complexity of this problem. Starting with the definition of the probability of the code matrix and the development of the likelihood of MPSK signals, it was possible to find an analytical solution for CDMA signals with a small code length. Averaging over matrices with the lowest Total Squared Correlation (TSC) allowed simplifying the equations for higher code lengths. The resulting algorithm was tested using Receiver Operating Characteristic Curves and Accuracy versus Signal-to-Noise Ratio (SNR). The algorithm that classifies CDMA in terms of code length and number of active users was extended to different complex types of CDMA under the assumptions of full-loaded, underloaded, balanced and unbalanced CDMA, for orthogonal or quasi-orthogonal codes, and chip-level synchronization.
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Abdelwahab, Manal M. "SELF DESIGNING PATTERN RECOGNITION SYSTEM EMPLOYING MULTISTAGE CLASSIFICATION." Doctoral diss., University of Central Florida, 2004. http://digital.library.ucf.edu/cdm/ref/collection/ETD/id/4479.
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Recently, pattern recognition/classification has received a considerable attention in diverse engineering fields such as biomedical imaging, speaker identification, fingerprint recognition, etc. In most of these applications, it is desirable to maintain the classification accuracy in the presence of corrupted and/or incomplete data. The quality of a given classification technique is measured by the computational complexity, execution time of algorithms, and the number of patterns that can be classified correctly despite any distortion. Some classification techniques that are introduced in the literature are described in Chapter one. In this dissertation, a pattern recognition approach that can be designed to have evolutionary learning by developing the features and selecting the criteria that are best suited for the recognition problem under consideration is proposed. Chapter two presents some of the features used in developing the set of criteria employed by the system to recognize different types of signals. It also presents some of the preprocessing techniques used by the system. The system operates in two modes, namely, the learning (training) mode, and the running mode. In the learning mode, the original and preprocessed signals are projected into different transform domains. The technique automatically tests many criteria over the range of parameters for each criterion. A large number of criteria are developed from the features extracted from these domains. The optimum set of criteria, satisfying specific conditions, is selected. This set of criteria is employed by the system to recognize the original or noisy signals in the running mode. The modes of operation and the classification structures employed by the system are described in details in Chapter three. The proposed pattern recognition system is capable of recognizing an enormously large number of patterns by virtue of the fact that it analyzes the signal in different domains and explores the distinguishing characteristics in each of these domains. In other words, this approach uses available information and extracts more characteristics from the signals, for classification purposes, by projecting the signal in different domains. Some experimental results are given in Chapter four showing the effect of using mathematical transforms in conjunction with preprocessing techniques on the classification accuracy. A comparison between some of the classification approaches, in terms of classification rate in case of distortion, is also given. A sample of experimental implementations is presented in chapter 5 and chapter 6 to illustrate the performance of the proposed pattern recognition system. Preliminary results given confirm the superior performance of the proposed technique relative to the single transform neural network and multi-input neural network approaches for image classification in the presence of additive noise.Ph.D.
Department of Electrical and Computer Engineering
Engineering and Computer Science
Engineering and Computer Science
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Huang, Jian Giles C. Lee. "A multiclass boosting classification method with active learning." [University Park, Pa.] : Pennsylvania State University, 2009. http://etda.libraries.psu.edu/theses/approved/WorldWideIndex/ETD-4765/index.html.
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Kaszycki, Gregory John. "An Adaptive Non-parametric Kernel Method for Classification." NCSU, 2000. http://www.lib.ncsu.edu/theses/available/etd-20000328-123728.
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One statistical method of estimating an underlying distribution from a set of samples is the non-parametric kernel method. This method can be used in classification toestimate the underlying distributions of the various classes. Since it can be shown that there is no perfect shape to a kernel function used to estimate an underlyingdistribution, several functions have been proposed and none is superior in all cases. This thesis demonstrates that a function can be created that adapts its shape to fitthe properties of the underlying data set. The function adapts its shape based on a pair of parameters and the algorithm uses a hill-climbing algorithm to determine thebest pair of parameters to use for the data set. This method gets consistently better accuracy than existing non-parametric kernel methods and comparable accuracy toother classification techniques.
In addition, this method can estimate information about the underlying characteristics of the data, based on the optimal parameters to thekernel function. This information includes the complexity of the underlying concept function and the general noise level in the measured attributes of the examples.
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Case, Simon James. "A fuzzy method for expression classification of faces." Thesis, University of Bristol, 2000. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.325907.
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Funai, Tomohiko. "Extensions of Nearest Shrunken Centroid Method for Classification." BYU ScholarsArchive, 2010. https://scholarsarchive.byu.edu/etd/2402.
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Stylometry assumes that the essence of the individual style of an author can be captured using a number of quantitative criteria, such as the relative frequencies of noncontextual words (e.g., or, the, and, etc.). Several statistical methodologies have been developed for authorship analysis. Jockers et al. (2009) utilize Nearest Shrunken Centroid (NSC) classification, a promising classification methodology in DNA microarray analysis for authorship analysis of the Book of Mormon. Schaalje et al. (2010) develop an extended NSC classification to remedy the problem of a missing author. Dabney (2005) and Koppel et al. (2009) suggest other modifications of NSC. This paper develops a full Bayesian classifier and compares its performance to five versions of the NSC classifier using the Federalist Papers, the Book of Mormon text blocks, and the texts of seven other authors. The full Bayesian classifier was superior to all other methods.
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MORGADO, WILSON LINS. "APPLYING RISK CLASSIFICATION METHOD IN CAR INSURANCE MARKET." PONTIFÍCIA UNIVERSIDADE CATÓLICA DO RIO DE JANEIRO, 2004. http://www.maxwell.vrac.puc-rio.br/Busca_etds.php?strSecao=resultado&nrSeq=5932@1.
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COORDENAÇÃO DE APERFEIÇOAMENTO DO PESSOAL DE ENSINO SUPERIORA estimação do risco em seguros de automóveis representa um difícil problema de regressão. As dificuldades vão desde a utilização de um grande número de variáveis discretas como explicativas, até a distribuição particular dos ruídos e uma quantidade expressiva de categorias com valores nulos e valores discrepantes. Supondo que os problemas de estimação estejam relacionados com a classificação do risco adotada pelo mercado, este trabalho propõe um método de classificação alternativo. O método desenvolvido foi baseado na técnica de análise fatorial, e no algoritmo de agrupamento de dados denominado fuzzy clustering system. Para avaliar a eficiência do método em solucionar os problemas de estimação, optou-se por utilizar o erro resultante da aplicação de modelos lineares generalizados. Ao final, o erro de estimação obtido diante da classificação proposta, foi comparado ao obtido diante da classificação usual de mercado.
The estimation of car insurance risk rate represents a difficult regression problem. One of the difficulties of this problem is the use of a number of discrete independent variables and a specific error distribution that presents an expressive number of null and outlier values. Assuming that these estimation problems are related to the risk classification adopted by the insurance companies, this work proposes an alternative classification method. This method is based on factorial analysis techniques and on the algorithm known as Fuzzy Clustering System. To evaluate the efficiency of this method in solving the problems identified, the risk was estimated using generalized linear models. The errors from each model were obtained and compared between classifications.
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Pics’, N. A., V. I. Mokryi, R. F. Fedoriv, and O. V. Cehelnik. "Method of classification of integumentary elements of landscape." Thesis, Вид-во СумДУ, 2006. http://essuir.sumdu.edu.ua/handle/123456789/11765.
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Silva, Glauco Barbosa da. "Combining data mining techniques with multicriteria decision aid in classification problems with composition probabilistc of preferences in trichotomic procedure (CPP-TRI)." Niterói, 2017. https://app.uff.br/riuff/handle/1/4079.
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Problem: From Modeling decision maker preferences, the Multicriteria Decision Aid (MCDA) is a field dedicated to the study of real-world decision-making problems that are, usually, too complex and not so well-structured to be considered through the examination of a single point of view (criteria). This feature of MCDA implies that a comprehensive model of a decision maker situation cannot be “created”, but instead, the model should be developed to meet the requirements of the Decision Maker (DM). In general, the development of such a model can only be achieved through an iterative and interactive process, until the preferences of the decision maker are consistently represented in the model. However, an interactive method is a procedure that consists of an alternation of calculation and discussion stages, which presumes that the decision maker is willing to answer a large number of relatively difficult questions. For instance, one of the main difficulties to be faced when interacting with a Decision Maker in order to build a decision aid procedure is the various parameters’ elicitation of the preference model. Methodology: In this thesis, as an alternative to interactive process, among the main streams of MCDA, a Preference Disaggregation Analysis method was used, which is considered to assess or to infer preference models from the given preferential structures and to address decision-aiding activities to elicit preferential information and to construct decision models from decision examples. Combining Composition Probabilistic of Preference with Data Mining techniques, a proposal of a three-step process is presented: attribute selection; clustering; and classification. The first and the second ones are data mining tasks and the last one is a multicriteria task. Purpose: This thesis aims to present a new approach with a Data Mining Layer (attribute selection and/or clustering) in Composition Probabilistic of Preferences in Trichotomic procedure (CPP-TRI), which combines data mining techniques with a Multicriteria Decision Aid method in classification (sorting) problems. Findings: The decision maker ability to comprehend without powerful tools has been exceeded. Therefore, important decisions are often made based not on the information-rich data stored in data repositories, but rather, on intuition of the decision maker. Involved in similar problems, the connections between disaggregation methods and data mining (identifying patterns, extracting knowledge from data, eliciting preferential information and constructing decision models from decision examples) are explored to combine and improve the CPP-TRI Method from Attribute Selection Techniques.
Problem: From Modeling decision maker preferences, the Multicriteria Decision Aid (MCDA) is a field dedicated to the study of real-world decision-making problems that are, usually, too complex and not so well-structured to be considered through the examination of a single point of view (criteria). This feature of MCDA implies that a comprehensive model of a decision maker situation cannot be “created”, but instead, the model should be developed to meet the requirements of the Decision Maker (DM). In general, the development of such a model can only be achieved through an iterative and interactive process, until the preferences of the decision maker are consistently represented in the model. However, an interactive method is a procedure that consists of an alternation of calculation and discussion stages, which presumes that the decision maker is willing to answer a large number of relatively difficult questions. For instance, one of the main difficulties to be faced when interacting with a Decision Maker in order to build a decision aid procedure is the various parameters’ elicitation of the preference model. Methodology: In this thesis, as an alternative to interactive process, among the main streams of MCDA, a Preference Disaggregation Analysis method was used, which is considered to assess or to infer preference models from the given preferential structures and to address decision-aiding activities to elicit preferential information and to construct decision models from decision examples. Combining Composition Probabilistic of Preference with Data Mining techniques, a proposal of a three-step process is presented: attribute selection; clustering; and classification. The first and the second ones are data mining tasks and the last one is a multicriteria task. Purpose: This thesis aims to present a new approach with a Data Mining Layer (attribute selection and/or clustering) in Composition Probabilistic of Preferences in Trichotomic procedure (CPP-TRI), which combines data mining techniques with a Multicriteria Decision Aid method in classification (sorting) problems. Findings: The decision maker ability to comprehend without powerful tools has been exceeded. Therefore, important decisions are often made based not on the information-rich data stored in data repositories, but rather, on intuition of the decision maker. Involved in similar problems, the connections between disaggregation methods and data mining (identifying patterns, extracting knowledge from data, eliciting preferential information and constructing decision models from decision examples) are explored to combine and improve the CPP-TRI Method from Attribute Selection Techniques.
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Tan, Mao. "A neural network method for generic edge feature classification." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 2000. http://www.collectionscanada.ca/obj/s4/f2/dsk1/tape2/PQDD_0029/MQ62367.pdf.
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Wei, Jinglun. "Classification of Bone Cements Using Multinomial Logistic Regression Method." Digital WPI, 2018. https://digitalcommons.wpi.edu/etd-theses/520.
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Bone cement surgery is a new technique widely used in medical field nowadays. In this thesis I analyze 48 bone cement types using their content of 20 elements. My goal is to ?find a method to classify new found bone cement sample into these 48 categories. Here I will use multinomial logistic regression method to see whether it works or not. Due to the lack of observations, I generate enough data by adding white noise in proper scales to the original data again and again, and then I get a data set of over 100 times as many points as the original one. Then I use purposeful variable selection method to pick the covariates I need, rather than stepwise selection. There are 15 covariates left after the selection, and then I use my new data set to fit such a multinomial logistic regression model. The model doesn't perform that good in goodness of ?fit test, but the result is still acceptable, and the diagnostic statistics also indicate a good performance. Combined with clinical experience and prior conditions, this model is helpful in this classification case.
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Goss, Ryan Gavin. "APIC: A method for automated pattern identification and classification." Doctoral thesis, University of Cape Town, 2017. http://hdl.handle.net/11427/27025.
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Machine Learning (ML) is a transformative technology at the forefront of many modern research endeavours. The technology is generating a tremendous amount of attention from researchers and practitioners, providing new approaches to solving complex classification and regression tasks. While concepts such as Deep Learning have existed for many years, the computational power for realising the utility of these algorithms in real-world applications has only recently become available. This dissertation investigated the efficacy of a novel, general method for deploying ML in a variety of complex tasks, where best feature selection, data-set labelling, model definition and training processes were determined automatically. Models were developed in an iterative fashion, evaluated using both training and validation data sets. The proposed method was evaluated using three distinct case studies, describing complex classification tasks often requiring significant input from human experts. The results achieved demonstrate that the proposed method compares with, and often outperforms, less general, comparable methods designed specifically for each task. Feature selection, data-set annotation, model design and training processes were optimised by the method, where less complex, comparatively accurate classifiers with lower dependency on computational power and human expert intervention were produced. In chapter 4, the proposed method demonstrated improved efficacy over comparable systems, automatically identifying and classifying complex application protocols traversing IP networks. In chapter 5, the proposed method was able to discriminate between normal and anomalous traffic, maintaining accuracy in excess of 99%, while reducing false alarms to a mere 0.08%. Finally, in chapter 6, the proposed method discovered more optimal classifiers than those implemented by comparable methods, with classification scores rivalling those achieved by state-of-the-art systems. The findings of this research concluded that developing a fully automated, general method, exhibiting efficacy in a wide variety of complex classification tasks with minimal expert intervention, was possible. The method and various artefacts produced in each case study of this dissertation are thus significant contributions to the field of ML.
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Eppe, Stefan. "Three contributions to the PROMETHEE II method." Doctoral thesis, Universite Libre de Bruxelles, 2015. http://hdl.handle.net/2013/ULB-DIPOT:oai:dipot.ulb.ac.be:2013/209033.
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PROMETHEE II is a widely used outranking method in the field of multi criteria decision aid (MCDA) method. The method outputs a ranking of a considered set of alternatives, based on the computation of net flow scores. In this thesis, aggregating several published journal articles and conference papers, we propose three contributions that relate to the method: 1) Outranking methods are based on the pairwise comparison of all considered alternatives, yielding a quadratic time complexity for evaluating the net flow scores. We propose a method for reducing to a linear time complexity and show that it offers good results; 2) Determining preference parameters, i.e. relative weights for each criterion, is not a trivial task. We propose two complementary approaches to eliciting preferences, based on the aggregation-disaggregation paradigm; 3) The phenomenon of rank reversal, that also affects the PROMETHEE II method, is often considered as problematic in the MCDA community. We formalise the exact conditions for rank reversal to occur with PROMETHEE II when adding or removing one or more alternatives to the original set. These conditions lead to the exact bound of rank reversal, a way to determine the actions that actually provoke rank reversal and two associated metrics that should be useful for concrete applications.
Doctorat en Sciences de l'ingénieur
info:eu-repo/semantics/nonPublished
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Burger, Christiaan. "A novel method of improving EEG signals for BCI classification." Thesis, Stellenbosch : Stellenbosch University, 2014. http://hdl.handle.net/10019.1/95984.
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Thesis (MEng)--Stellenbosch University, 2014.ENGLISH ABSTRACT: Muscular dystrophy, spinal cord injury, or amyotrophic lateral sclerosis (ALS) are injuries and disorders that disrupts the neuromuscular channels of the human body thus prohibiting the brain from controlling the body. Brain computer interface (BCI) allows individuals to bypass the neuromuscular channels and interact with the environment using the brain. The system relies on the user manipulating his neural activity in order to control an external device. Electroencephalography (EEG) is a cheap, non-invasive, real time acquisition device used in BCI applications to record neural activity. However, noise, known as artifacts, can contaminate the recording, thus distorting the true neural activity. Eye blinks are a common source of artifacts present in EEG recordings. Due to its large amplitude it greatly distorts the EEG data making it difficult to interpret data for BCI applications. This study proposes a new combination of techniques to detect and correct eye blink artifacts to improve the quality of EEG for BCI applications. Independent component analysis (ICA) is used to separate the EEG signals into independent source components. The source component containing eye blink artifacts are corrected by detecting each eye blink within the source component and using a trained wavelet neural network (WNN) to correct only a segment of the source component containing the eye blink artifact. Afterwards, the EEG is reconstructed without distorting or removing the source component. The results show a 91.1% detection rate and a 97.9% correction rate for all detected eye blinks. Furthermore for channels located over the frontal lobe, eye blink artifacts are corrected preserving the neural activity. The novel combination overall reduces EEG information lost, when compared to existing literature, and is a step towards improving EEG pre-processing in order to provide cleaner EEG data for BCI applications.
AFRIKAANSE OPSOMMING: Spierdistrofie, ’n rugmurgbesering, of amiotrofiese laterale sklerose (ALS) is beserings en steurnisse wat die neuromuskulêre kanale van die menslike liggaam ontwrig en dus verhoed dat die brein die liggaam beheer. ’n Breinrekenaarkoppelvlak laat toe dat die neuromuskulêre kanale omlei word en op die omgewing reageer deur die brein. Die BCI-stelsel vertrou op die gebruiker wat sy eie senuwee-aktiwiteit manipuleer om sodoende ’n eksterne toestel te beheer. Elektro-enkefalografie (EEG) is ’n goedkoop, nie-indringende, intydse dataverkrygingstoestel wat gebruik word in BCI toepassings. Nie net senuwee aktiwiteit nie, maar ook geraas , bekend as artefakte word opgeneem, wat dus die ware senuwee aktiwiteit versteur. Oogknip artefakte is een van die algemene artefakte wat teenwoordig is in EEG opnames. Die groot omvang van hierdie artefakte verwring die EEG data wat dit moeilik maak om die data te ontleed vir BCI toepassings. Die studie stel ’n nuwe kombinasie tegnieke voor wat oogknip artefakte waarneem en regstel om sodoende die kwaliteit van ’n EEG vir BCI toepassings te verbeter. Onafhanklike onderdeel analise (Independent component analysis (ICA)) word gebruik om die EEG seine te skei na onafhanklike bron-komponente. Die bronkomponent wat oogknip artefakte bevat word reggestel binne die komponent en gebruik ’n ervare/geoefende golfsenuwee-netwerk om slegs ’n deel van die komponent wat die oogknip artefak bevat reg te stel. Daarna word die EEG hervorm sonder verwringing of om die bron-komponent te verwyder. Die resultate toon ’n 91.1% opsporingskoers en ’n 97.9% regstellingskoers vir alle waarneembare oogknippe. Oogknip artefakte in kanale op die voorste lob word reggestel en behou die senuwee aktiwiteit wat die oorhoofse EEG kwaliteit vir BCI toepassings verhoog.
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Daura, Ashiru Sani. "A wavelet-based method for the classification of PCG signals." Thesis, University of Newcastle Upon Tyne, 1998. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.244474.
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Wan, Fengkai. "Deep Learning Method used in Skin Lesions Segmentation and Classification." Thesis, KTH, Medicinsk teknik, 2018. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-233467.
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Malignant melanoma (MM) is a type of skin cancer that is associated with a very poor prognosis and can often lead to death. Early detection is crucial in order to administer the right treatment successfully but currently requires the expertise of a dermatologist. In the past years, studies have shown that automatic detection of MM is possible through computer vision and machine learning methods. Skin lesion segmentation and classification are the key methods in supporting automatic detection of different skin lesions. Compared with traditional computer vision as well as other machine learning methods, deep neural networks currently show the greatest promise both in segmentation and classification. In our work, we have implemented several deep neural networks to achieve the goals of skin lesion segmentation and classification. We have also applied different training schemes. Our best segmentation model achieves pixel-wise accuracy of \textbf{0.940}, Dice index of \textbf{0.867} and Jaccard index of \textbf{0.765} on the ISIC 2017 challenge dataset. This surpassed the official state of the art model whose pixel-wise accuracy was 0.934, Dice index 0.849 and Jaccard Index 0.765. We have also trained a segmentation model with the help of adversarial loss which improved the baseline model slightly. Our experiments with several neural network models for skin lesion classification achieved varying results. We also combined both segmentation and classification in one pipeline meaning that we were able to train the most promising classification model on pre-segmented images. This resulted in improved classification performance. The binary (melanoma or not) classification from this single model trained without extra data and clinical information reaches an area under the curve (AUC) of 0.684 on the official ISIC test dataset. Our results suggest that automatic detection of skin cancers through image analysis shows significant promise in early detection of malignant melanoma.
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Kurujyibwami, Célestin. "Group classification of linear Schrödinger equations by the algebraic method." Licentiate thesis, Linköpings universitet, Matematiska institutionen, 2016. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-125136.
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This thesis is devoted to the group classification of linear Schrödinger equations. The study of Lie symmetries of such equations was initiated more than 40 years ago using the classical Lie infinitesimal method for specific types of real-valued potentials. In first papers on this subject, most attention was paid to dynamical transformations, which necessarily change the time and space variables. This is why phase translations were missed. Later, the study of Lie symmetries was extended to nonlinear Schrödinger equations. At the same time, the group classification problem for the class of linear Schrödinger equations with complex potentials remains unsolved. The aim of the present thesis is to carry out the group classification for the class of linear Schrödinger equations with complex potentials. These potentials are nowadays important in quantum mechanics, scattering theory, condensed matter physics, quantum field theory, optics, electromagnetics and so forth. We exhaustively solve the group classification problem for space dimensions one and two. The thesis comprises two parts. The first part is a brief review of Lie symmetries and group classification of differential equations. Next, we outline the equivalence transformations in a class of differential equations, normalization properties of such class and the algebraic method for group classification of differential equations. The second part consists of two research papers. In the first paper, the algebraic method is applied to solve the group classification problem for (1+1)-dimensional linear Schrödinger equations with complex potentials. With this technique, the problem of the group classification of the class under study is reduced to the classification of certain subalgebras of its equivalence algebra. As a result, we find that the inequivalent cases are exhausted by eight families of potentials and we give the corresponding maximal Lie invariance algebras. In the second paper we carry out the preliminary symmetry analysis of the class of linear Schrödinger equations with complex potentials in the multi-dimensional case. Using the direct method, we find the equivalence groupoid and the equivalence group of this class. Due to the multi-dimensionality, the results of the computations are quite different from the ones presented in Paper I. We obtain the complete group classification of (1+2)-dimensional linear Schrödinger equations with complex potentials.
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Wood, Nicholas Linder. "A Novel Kernel-Based Classification Method using the Pythagorean Theorem." The Ohio State University, 2016. http://rave.ohiolink.edu/etdc/view?acc_num=osu1462522255.
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Pan, Yi. "A Proposed Frequency-Based Feature Selection Method for Cancer Classification." TopSCHOLAR®, 2017. http://digitalcommons.wku.edu/theses/1954.
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Feature selection method is becoming an essential procedure in data preprocessing step. The feature selection problem can affect the efficiency and accuracy of classification models. Therefore, it also relates to whether a classification model can have a reliable performance. In this study, we compared an original feature selection method and a proposed frequency-based feature selection method with four classification models and three filter-based ranking techniques using a cancer dataset. The proposed method was implemented in WEKA which is an open source software. The performance is evaluated by two evaluation methods: Recall and Receiver Operating Characteristic (ROC). Finally, we found the frequency-based feature selection method performed better than the original ranking method.
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Cazzanti, Luca. "Generative models of similarity-based classification /." Thesis, Connect to this title online; UW restricted, 2007. http://hdl.handle.net/1773/5905.
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Μαστρογιάννης, Νικόλαος. "Μεθοδολογικό πλαίσιο υποστήριξης της εξόρυξης γνώσης από δεδομένα με την χρήση αρχών της πολυκριτήριας ανάλυσης αποφάσεων." Thesis, 2009. http://nemertes.lis.upatras.gr/jspui/handle/10889/2506.
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Η εξόρυξη γνώση από δεδομένα είναι μια νέα και δυναμική τεχνολογία που βοηθάει τις επιχειρήσεις να επικεντρωθούν στην σημαντική πληροφορία που βρίσκεται μέσα στις αποθήκες δεδομένων τους, αναζητώντας κρυμμένα πρότυπα και ανακαλύπτοντας πληροφορίες που οι ειδικοί μπορεί να χάσουν ή να παραβλέψουν. Τα τελευταία χρόνια έχει αναπτυχθεί πλήθος αλγορίθμων της εξόρυξης δεδομένων, οι οποίοι ακολουθούν διαφορετικές μεθοδολογικές προσεγγίσεις, ενώ ταυτόχρονα παρουσιάζουν σημαντική ποικιλία εφαρμογών. Η προσπάθεια ωστόσο για βελτιωμένους και αποδοτικότερους αλγορίθμους συνεχίζεται.
Η παρούσα διδακτορική διατριβή έχει σαν βασικό της στόχο να συνεισφέρει στην προσπάθεια αυτή, βελτιώνοντας και ενισχύοντας την θεωρητική θεμελίωση υφιστάμενων αλγορίθμων της εξόρυξης δεδομένων. Ειδικότερα, μέσα από μια διαφορετική λογική, η οποία βασίζεται σε έννοιες και διαδικασίες της πολυκριτήριας ανάλυσης αποφάσεων, και ειδικότερα της μεθόδου ELECTRE I της θεωρίας των σχέσεων υπεροχής, η διδακτορική διατριβή αναπτύσσει ένα νέο μεθοδολογικό πλαίσιο για την εξόρυξη δεδομένων. Ενσωματώνοντας στην συνέχεια αυτό το μεθοδολογικό πλαίσιο σε υφιστάμενους αλγορίθμους, δημιουργούνται ουσιαστικά νέοι, αποτελεσματικότεροι και ακριβέστεροι αλγόριθμοι, για επιμέρους διαδικασίες και εφαρμογές της εξόρυξης δεδομένων.
Πιο συγκεκριμένα, το προτεινόμενο μεθοδολογικό πλαίσιο, εφαρμόστηκε, με τις αναγκαίες τροποποιήσεις, στις διαδικασίες της ταξινόμησης και της ομαδοποίησης κατηγορικών αντικειμένων, μέσω των μεθόδων CLEDM και CLEKMODES, αντίστοιχα. Τα καλά αποτελέσματα από την εφαρμογή των παραπάνω μεθόδων σε μια σειρά ευρέως χρησιμοποιούμενων βάσεων δεδομένων, σε συνδυασμό με την δυνατότητα επέκτασης του μεθοδολογικού πλαισίου και σε άλλες διαδικασίες της εξόρυξης δεδομένων, διαμορφώνουν ένα νέο «υβριδικό» πεδίο έρευνας. Το πεδίο αυτό, αφενός έχει την δυναμική παραγωγής συνεχώς καλύτερων αλγορίθμων για την εξόρυξη δεδομένων, αφετέρου μπορεί να εξερευνήσει εις βάθος και να τυποποιήσει περαιτέρω την αλληλεπίδραση της εξόρυξης δεδομένων με την πολυκριτήρια ανάλυση αποφάσεων.Data mining is a new and advancing technology that helps corporations to focus on the most important pieces of information stored in their data warehouses. In particular, data mining searches for hidden patterns and is able to discover information that otherwise could be missed or overlooked by experts. During the last years, a series of data mining algorithms has been developed. These algorithms are based on different methodological patterns and they can be implemented to solve a large variety of applications. However, the effort to build more advanced and efficient data mining algorithms has never stopped. The goal of this PhD thesis is to significantly contribute to the above effort by enhancing and improving the theoretical framework of existing data mining algorithms. More specifically, a different theoretical perspective is introduced, that is based on concepts and procedures of multicriteria analysis and in particular the ELECTRE I method of the outranking relations theory. Consequently, the PhD thesis develops a new methodological framework for data mining that can be incorporated to existing algorithms. This incorporation essentially develops new, more effective and accurate data mining algorithms, for a series of tasks and applications. In particular, the proposed methodological framework was applied, properly modified, to the tasks of classification and clustering, through the CLEDM and CLEKMODES methods, respectively. The good results of these methods in a series of widely used databases, and the perspective of expanding the new methodological framework to other data mining tasks as well, are able to introduce a new “hybrid” research field. This research field has the potential of producing better data mining algorithms and furthermore the potential to thoroughly explore and further formalize the interaction of data mining and multicriteria analysis.
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Chang, Hao-Chun, and 張浩鈞. "A Qualitative Multicriteria Evaluation Method with Effectiveness Measurement." Thesis, 2000. http://ndltd.ncl.edu.tw/handle/64274641741814171963.
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碩士華梵大學
工業管理學系碩士班
88
This study proposes a qualitative multicriteria evaluation method to evaluating qualitative decision problems with multiple qualitative criteria and multiple decision-makers/experts. In the proposed method, the criteria weights and performance values are measured by category and ordinal scale, the consensus weights and performance values for multiple decision-makers/experts are determined by majority rule. There are essentially two structural types of evaluation criteria: no hierarchical structure and hierarchical structure. From the related studies of the past two decades, most of qualitative multicriteria evaluation problems used three or four levels criteria hierarchies. Therefore, according to the analytical logic of hierarchical criteria weighted summation, which are use of scoring technique, this study presents ordinal criteria weighted summation procedure to analyzing evaluation criteria weights with hierarchical structure. To verify the effectiveness of the proposed method, twenty cases of the past research are compared for criteria with hierarchical structure and simulation analysis for criteria with no hierarchy. From the Spearman’s rank correlation test results, the consistency ratio of ranking between AHP or SAW method and the proposed method are approximate 0.8. Finally, two empirical multicriteria evaluation examples are provided: port competition evaluation for Pacific-Asia areas and privatization decision for port facilities investment. In accordance with the effectiveness measurement and empirical studies, the proposed method in this study is a useful multicriteria evaluation method for practical decision problems.
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Sebastião, Rui Pedro Rodrigues. "Solving unstructured classification problems with multicriteria decision aiding." Dissertação, 2011. http://hdl.handle.net/10216/61685.
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Sebastião, Rui Pedro Rodrigues. "Solving unstructured classification problems with multicriteria decision aiding." Master's thesis, 2011. http://hdl.handle.net/10216/61685.
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Chou, Hsing-Fu, and 周信甫. "Application of Fuzzy Multicriteria Evaluation Method to Domestic Equity Funds Investment." Thesis, 2008. http://ndltd.ncl.edu.tw/handle/30185977116664632351.
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碩士華梵大學
工業工程與經營資訊學系碩士班
96
In recent years, mutual funds are very popular and become one way of investments and financial management. However, a busy investor usually could not make correct judgment in respect of fund selections and therefore resulting in lower investment outcome. Thus, it is very essential for investors to make good choices and evaluations to fund investments. This study selected the domestic equity funds from professional perspective to proceed research and analysis based on Fuzzy Multi-Criteria Decision Making (FMCDM). The brainstorming method was adopted to integrate relevant elements in different hierarchies evaluated by professionals into three evaluation periods, five evaluation aspects, fourteen evaluation standards and three feasible plans beneath the goal. The pair-wise comparison of Analytic Hierarchy Process (AHP) was adopted to proceed questionnaire survey and cooperated with Fuzzy Analytic Hierarchy Process (FAHP) after integration by Triangular Fuzzy Number (TFN). Then, associate important elements in different hierarchies were selected through the order by defuzzy via center of gravity method and normalization process. Finally, the overall best investment project was evaluated through rating by series of hierarchical and the sums. According to the result of empirical research, there are Lump Sum (LS), Dollar-Cost Averaging (DCA) and Value Averaging (VA) such three feasible plans available for domestic equity funds evaluations, while the VA would be the best choice for investment.
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LinMin-Da and 林明達. "Exploring the Multicriteria Evaluation Index of Firm's Value by Qualitative Method ─Intellectual Capital Perspectives." Thesis, 2006. http://ndltd.ncl.edu.tw/handle/34537435126969295197.
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碩士崑山科技大學
企業管理研究所
94
Most of measures in the past to evaluate the performance of business were indicated by financial statement. With the arrival of the era of knowledge-driven economy, however, it couldn’t completely assess the whole true valuation of business in terms of financial statement which was the core on evaluated the tangible capital traditionally, will make a great deal of gaps between market price and book value for company. On weigh enterprise value, it seems to appears that non-financial index have offered more powerful direction on evaluate competitive advantage of business, is the true and real value for company. A non- financial statement index which can’t be show up on financial statement is named Intellectual Capital (IC). Because of the instability and unmeasurement of some intangible capital on future benefit., how with the intellectual capital should to make to weigh enterprise's value and manage the performance has became a studying topic. The existing research is mostly based on quantization index, different from the past, this text was to adopt quality research approach, using depth interview with the president, general manager and assistant manager whose company were listed or went to the cupboard company which have been the indicator on the market, In order to analyze the text material, assisting with the hermeneutic cycle principle of theme analyses. the analysis result is summed up the main commenting amount index: (1) Under the kownledge economy, someone has wealth then; (2) The whole joint-venture source , create the advantage ; (3) Gather together to The Blue Ocean, surmount the competition; (4) The rain and dew is dipped in , form good reason in GuangZhou; (5) Invisible assets, the influence that can be seen.
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Lan, Tzu-Chun, and 藍子鈞. "Multicriteria Decision Making Based on the TOPSIS Method and Similarity Measures Between Intuitionistic Fuzzy Sets." Thesis, 2015. http://ndltd.ncl.edu.tw/handle/29321928922507566564.
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碩士國立臺灣科技大學
資訊工程系
103
Multicriteria decision making based on intuitionistic fuzzy sets is an important research topic. In recent years, some methods have been presented for multicriteria decision making based on intuitionistic fuzzy sets. In this thesis, we propose a new similarity measure between intuitionistic fuzzy sets based on the centroid points of the transformed right-angled triangular fuzzy numbers and prove some properties of the proposed similarity measure between intuitionistic fuzzy values. Then, we propose a new multicriteria decision making method based on the TOPSIS method and the proposed similarity measure between intuitionistic fuzzy sets to overcome the drawbacks of the existing methods, where the existing methods have the drawbacks that they cannot get the preference order of alternatives in some situations due to the fact that they have “the division by zero problem”. We also use some examples to illustrate the proposed multicriteria decision making method can overcome the drawbacks of the existing methods. The proposed multicriteria decision making method provides us with a useful way for multicriteria decision making in intuitionistic fuzzy environments.
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Huang, Yu-hua, and 黃俞華. "Data Classification via Network Method." Thesis, 2016. http://ndltd.ncl.edu.tw/handle/15835881768020796471.
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碩士國立高雄大學
統計學研究所博士班
104
The results of classification of traditional data are frequently limited to the choice of the distance. We provide a new concept of converting the traditional data into a network, and then using the network clustering technology to obtain the result of classification. First, we extend information of each data and treat it as a node of the network. Second, use the multivariate two-sample test method to determine whether two nodes have a link between them. Finally, we cluster this network. The empirical results show that our method has a relatively stable clustering effect.
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AndyDon and 董俊展. "A Classification Method for Numerical Datasets." Thesis, 2001. http://ndltd.ncl.edu.tw/handle/55367919849800535296.
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碩士輔仁大學
資訊工程學系
89
A classification algorithm can predict the class of new instances based on the training data. Many classification algorithms work most naturally with nominal attributes. However, numerical data are very common in real-life applications. When all the attributes are numerical in the training data, statistics methods are natural techniques to consider. In this research, we first apply the technique of factor analysis in statistics to find the interdependence among the attributes. We then adopt the idea of the function decomposition to simplify the problem. Finally, we propose an approach, which we call ER algorithm, to find the immediate function values of the training data. The entire work of these processes provides a classification algorithm for numerical datasets. Experiments show that the performance of prediction is satisfied.
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Lai, Jung-Yao, and 賴榮耀. "The Application of Fuzzy Multicriteria Decision Making Method on Master Production Scheduling Techniques for Assemble-To- Order Products." Thesis, 1993. http://ndltd.ncl.edu.tw/handle/43962159750641134576.
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碩士國立交通大學
資訊管理研究所
81
The primary objective of this study is to integrate data base system , expert system and fuzzy multicriteria decision making method to implement a master production scheduling techniques decision system(MPSTDS) for assemble-to-order(ATO) products. Automobiles and personal computers are examples of ATO products . The ATO company sells a wide variety of customized products requiring some customer interface regarding product specifications . Competition may exist among the producers of similar products such that the firms'' sales volumes may be seriously affected by variations in quality, price,lead tile..etc. This paper proposes the MPSTDS to support the manufacture manager who can dynamically select the best suitable technique for designing a master production scheduling that according to current marketing demand , product structure type and company manufacturing stategy. Multicriteria decision making bas been one of rapid growing research areas in evaluation method . This method cooperate with fuzzy inference used to determine the best suitable technique for ATO firms. Additionally, this study uses the expert system development shell - LEVEL 5 OBJECT , dBASE III Plus and CLIPPER lanauage to develop a MPSTDS prototype system and to verify the MPSTDS. Keyword : Master Production Scheduling , Fuzzy inference , Multicriteria decision making
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Po-AnLin and 林柏安. "A Hybrid Classification Method for Conference Information." Thesis, 2012. http://ndltd.ncl.edu.tw/handle/11565827412416413748.
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碩士國立成功大學
資訊管理研究所
100
There are many researchers who want to realize the latest research topic and exchange information with others. They will surf the Internet for scholar conference information, and choose some of them to attend. Some websites have provided part of conference information, but most of them cannot help users find the information users really want to explore; besides, it is a hard work to filter the searched conference information by human. Hence, it is an important issue to help reseachers find out the suited conference information from the huge dataset to attend. To find out the suited conference information efficiently for researcher, this study will classify the conference by text mining. The previous references of traditional classification algorithm like Decision Tree, Naïve Bayes Classifier and Support Vector Machine are not designed to classify documents of conference information, so when we classify these academic documents, we may get some incorrect answers. Therefore, the goal of this study is designing a classification algorithm for conference information. Because there are many terminology nouns or phrases which consist of two words in the conference, when we analyze the importance of the terms, we should take this situation into consideration. Moreover, there are pros and cons in different existing classification algorithms, so the hybrid classification is adopted to integrate the traditional algorithm. We expect the new method designing for conference information can help researchers find the suited conferences efficiently and exactly.
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Su, Yun-Hsuan, and 蘇韻璇. "Brain MRI tissue classification using SGA method." Thesis, 2015. http://ndltd.ncl.edu.tw/handle/46039389813487651585.
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碩士國立中興大學
電機工程學系所
103
In recent years, thanks to the advances of medical technology, brain disease is no longer a desperate end. Different diseases could affect gray-matter and white-matter change unpredictably, hence may cause brain lesion and brain degeneration differently. Therefore, how to segment the lesion efficiently and accurately is an important issue. Fortunately, it was due to thousands of non-intrusive inspections that doctors don''t have to cut through the skin and muscle to confirm the lesion location. The most important and widely used non-intrusive inspections is using magnetic resonance imaging (MRI) technique. In this thesis we propose a SGA method for brain MRI tissue classification. Classification algorithm generally requires a set of training samples to carry out in a supervised or an unsupervised manner depending upon how the training samples are produced a priori using prior knowledge or a posteriori obtained directly from the data. In this thesis, we present an unsupervised simplex growing algorithm (SGA) to find initial training sample. The initial training sample then combine with spectral angle mapping (SAM) technology to expand bands and regenerate a set of training samples. Then we apply constrained energy minimization (CEM) method to highlight the location of lesions. After all that work, we use Otsu''s method to calculate an appropriate threshold from the brain web image. The detection results that using SGA collocation with SAM method to expand bands, even if in the high noise surrounding, are better than the method using ATGP. Experiment results show that these approaches have greater promise in MR image classification than Chih-Kai Chang proposed thesis in 2013.
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Bi-NaWu and 伍碧那. "A hybrid discretization method for classification algorithms." Thesis, 2014. http://ndltd.ncl.edu.tw/handle/89127564223669943961.
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碩士國立成功大學
資訊管理研究所
102
Discretization is one of the major approaches for processing continuous attributes for classifiers. Hybrid discretization sets the method for discretizing each continuous attribute individually. A previous study found that hybrid discretization method is a better approach to improve the performance of naïve Bayesian classifier than unified discretization. That approach determines the discretization method for each attribute based on whether accuracy can be improved or not. The objectives of this study is to develop a hybrid discretization method applicable for classifiers such that it can determine the discretization method for each attribute in data preprocessing step instead of using accuracy. This study will first build a network optimization models based on the association among attributes and the class. Dynamic programming is then employed to find the optimal solution for the network, and this solution indicates the discretization method for each continuous attribute. The classification tools for testing our methods are decision trees, naïve Bayesian classifiers, and rule-based classifiers. The experimental results on 20 data sets show that the computational cost of our method is low, and that in general, the hybrid discretization method have a better performance in naïve Bayesian classifiers and rule-based classifiers, but not in decision trees.
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Wu, Ming-Chang, and 吳明昌. "OWA based Clustering method for classification problem." Thesis, 2007. http://ndltd.ncl.edu.tw/handle/68953933170960741609.
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碩士國立雲林科技大學
資訊管理系碩士班
95
Information classification plays an important role in decision-making problems. As information technology advances, large amounts of information stored in database. Data preprocessing is necessary because some data is dirty. Many tasks are worked out in high complexity and dimensionality in classification problem. Therefore, we apply ordered weighted averaging (OWA) operator to fusion multi-attribute data into the aggregated values of single attribute, and cluster the aggregated values for classification tasks. The proposed method consists of four steps: (1) use stepwise regression to select and order the important attribute, (2) utilize OWA operator to get aggregated values of single attribute from multi-attribute data, (3) cluster the aggregated values by K-Means method, (4) predict the clusters of testing data. In verification and comparison, three datasets: (1) Iris, (2) Wisconsin-breast-cancer and (3) Key Performance Indicators datasets are conducted by the proposed method. The problems of high complexity and dimensionality are solved and the classification accuracy rate is higher than some existing methods.
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Wang, Chang-Wei, and 王常威. "A content-based XML document classification method." Thesis, 2004. http://ndltd.ncl.edu.tw/handle/03399576694192114184.
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Ciou, Jhih-yuan, and 邱智遠. "Fusion of Lidar Height Data for Urban Feature Classification Using Hybrid Classification Method." Thesis, 2008. http://ndltd.ncl.edu.tw/handle/9e2yqw.
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碩士國立中山大學
海洋環境及工程學系研究所
96
In recent years, many researches focused on the supervised machine learning classification methods using Lidar and remotely sensed image to provide buildings, trees, roads, and grass categories for urban ground feature classification. First, this research performed urban ground feature classification based on true color aerial imagey and Lidar Intensity. Second, Lidar derived normalized DSM (nDSM) was added to the classification. Finally, the concept of height level rules was applied. This research utilized two-level height rule-based classification exteneded from three-level height rule-based classification (Huang, 2007). It is obvious to observ the overlap for the roads and houses, and grass and trees in the feature space plot where result in the classification confusion. These confusions can be resolved by fusion the height information. After comparing classification accuracy, the two-level height is better than three-level height classification scheme. This research proposed hybrid classification method based on Maximum likelihood classification (MLC) and two-level height rules. This method reveals the role of height information in urban ground feature classification. The height level rules were also applied to other supervised classification method such as Back-Propagation Network (BPN) and Support Vector Machine (SVM). The classification results show that the accuracy of hybrid method is better than the orgional classification method. However, the time required to look for the classification parameters for BPN and SVM is greater than MLC but only can derived considerable results. Therefore, the hybrid classification method based on MLC is better than other two methods.