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Novi, Daniele. "Knowledge management and Discovery for advanced Enterprise Knowledge Engineering." Doctoral thesis, Universita degli studi di Salerno, 2014. http://hdl.handle.net/10556/1466.
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2012 - 2013The research work addresses mainly issues related to the adoption of models, methodologies and knowledge management tools that implement a pervasive use of the latest technologies in the area of Semantic Web for the improvement of business processes and Enterprise 2.0 applications. The first phase of the research has focused on the study and analysis of the state of the art and the problems of Knowledge Discovery database, paying more attention to the data mining systems. The most innovative approaches which were investigated for the "Enterprise Knowledge Engineering" are listed below. In detail, the problems analyzed are those relating to architectural aspects and the integration of Legacy Systems (or not). The contribution of research that is intended to give, consists in the identification and definition of a uniform and general model, a "Knowledge Enterprise Model", the original model with respect to the canonical approaches of enterprise architecture (for example with respect to the Object Management - OMG - standard). The introduction of the tools and principles of Enterprise 2.0 in the company have been investigated and, simultaneously, Semantic Enterprise based appropriate solutions have been defined to the problem of fragmentation of information and improvement of the process of knowledge discovery and functional knowledge sharing. All studies and analysis are finalized and validated by defining a methodology and related software tools to support, for the improvement of processes related to the life cycles of best practices across the enterprise. Collaborative tools, knowledge modeling, algorithms, knowledge discovery and extraction are applied synergistically to support these processes. [edited by author]
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Nica, Cristina. "Exploring sequential data with relational concept analysis." Thesis, Strasbourg, 2017. http://www.theses.fr/2017STRAD032/document.
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De nombreuses méthodes d’extraction de motifs séquentiels ont été proposées pour découvrir des motifs utiles qui décrivent les données analysées. Certaines de ces travaux se sont concentrés sur l’énumération efficace de motifs partiellement ordonnés fermés (cpo-motifs), ce qui rend leur évaluation difficile pour les experts, car leur nombre peut être important. Par suite, nous proposons une approche nouvelle, qui consiste à extraire directement des cpo-motifs multi-niveaux qui sont organisés dans une hiérarchie. Nous proposons une méthode originale dans la cadre de l’Analyse Relationnelle de Concepts (ARC), appelée RCA-SEQ, qui exploite la structure et les propriétés des treillis issus de l’ARC. RCA-SEQ comporte cinq étapes : le prétraitement des données ; l'exploration par l’ARC des données ; l'extraction automatisée d'une hiérarchie de cpo-motifs multi-niveaux par navigation des treillis issus de l’ARC ; la sélection de cpo-motifs pertinents ; l'évaluation des motifs par les expertsMany sequential pattern mining methods have been proposed to discover useful patterns that describe the analysed sequential data. Several of these works have focused on efficiently enumerating all closed partially-ordered patterns (cpo-patterns), that makes their evaluation a laboured task for experts since their number can be large. To address this issue, we propose a new approach, that is to directly extract multilevel cpo-patterns implicitly organised into a hierarchy. To this end, we devise an original method within the Relational Concept Analysis (RCA) framework, referred to as RCA-SEQ, that exploits the structure and properties of the lattices from the RCA output. RCA-SEQ spans five steps: the preprocessing of the raw data; the RCA-based exploration of the preprocessed data; the automatic extraction of a hierarchy of multilevel cpo-patterns by navigating the lattices from the RCA output; the selection of relevant multilevel cpo-patterns; the pattern evaluation done by experts
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De, Maio Carmen. "Fuzzy concept analysis for semantic knowledge extraction." Doctoral thesis, Universita degli studi di Salerno, 2012. http://hdl.handle.net/10556/1307.
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2010 - 2011Availability of controlled vocabularies, ontologies, and so on is enabling feature to provide some added values in terms of knowledge management. Nevertheless, the design, maintenance and construction of domain ontologies are a human intensive and time consuming task. The Knowledge Extraction consists of automatic techniques aimed to identify and to define relevant concepts and relations of the domain of interest by analyzing structured (relational databases, XML) and unstructured (text, documents, images) sources. Specifically, methodology for knowledge extraction defined in this research work is aimed at enabling automatic ontology/taxonomy construction from existing resources in order to obtain useful information. For instance, the experimental results take into account data produced with Web 2.0 tools (e.g., RSS-Feed, Enterprise Wiki, Corporate Blog, etc.), text documents, and so on. Final results of Knowledge Extraction methodology are taxonomies or ontologies represented in a machine oriented manner by means of semantic web technologies, such as: RDFS, OWL and SKOS. The resulting knowledge models have been applied to different goals. On the one hand, the methodology has been applied in order to extract ontologies and taxonomies and to semantically annotate text. On the other hand, the resulting ontologies and taxonomies are exploited in order to enhance information retrieval performance and to categorize incoming data and to provide an easy way to find interesting resources (such as faceted browsing). Specifically, following objectives have been addressed in this research work: Ontology/Taxonomy Extraction: that concerns to automatic extraction of hierarchical conceptualizations (i.e., taxonomies) and relations expressed by means typical description logic constructs (i.e., ontologies). Information Retrieval: definition of a technique to perform concept-based the retrieval of information according to the user queries. Faceted Browsing: in order to automatically provide faceted browsing capabilities according to the categorization of the extracted contents. Semantic Annotation: definition of a text analysis process, aimed to automatically annotate subjects and predicates identified. The experimental results have been obtained in some application domains: e-learning, enterprise human resource management, clinical decision support system. Future challenges go in the following directions: investigate approaches to support ontology alignment and merging applied to knowledge management.
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Kanade, Parag M. "Fuzzy ants as a clustering concept." [Tampa, Fla.] : University of South Florida, 2004. http://purl.fcla.edu/fcla/etd/SFE0000397.
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Rudolph, Sebastian. "Relational Exploration: Combining Description Logics and Formal Concept Analysis for Knowledge Specification." Doctoral thesis, Technische Universität Dresden, 2006. https://tud.qucosa.de/id/qucosa%3A25002.
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Facing the growing amount of information in today's society, the task of specifying human knowledge in a way that can be unambiguously processed by computers becomes more and more important. Two acknowledged fields in this evolving scientific area of Knowledge Representation are Description Logics (DL) and Formal Concept Analysis (FCA). While DL concentrates on characterizing domains via logical statements and inferring knowledge from these characterizations, FCA builds conceptual hierarchies on the basis of present data. This work introduces Relational Exploration, a method for acquiring complete relational knowledge about a domain of interest by successively consulting a domain expert without ever asking redundant questions. This is achieved by combining DL and FCA: DL formalisms are used for defining FCA attributes while FCA exploration techniques are deployed to obtain or refine DL knowledge specifications.
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Konecny, Jan. "Isotone fuzzy Galois connections and their applications in formal concept analysis." Diss., Online access via UMI:, 2009.
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Thesis (Ph. D.)--State University of New York at Binghamton, Thomas J. Watson School of Engineering and Applied Science, Department of Systems Science and Industrial Engineering, 2009.Includes bibliographical references.
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Rudolph, Sebastian [Verfasser]. "Relational exploration : combining description logics and formal concept analysis for knowledge specification / von Sebastian Rudolph." Karlsruhe : Univ.-Verl. Karlsruhe, 2007. http://d-nb.info/983756430/34.
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Rudolph, Sebastian. "Relational Exploration." Doctoral thesis, Saechsische Landesbibliothek- Staats- und Universitaetsbibliothek Dresden, 2007. http://nbn-resolving.de/urn:nbn:de:swb:14-1172682174599-12286.
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Facing the growing amount of information in today's society, the task of specifying human knowledge in a way that can be unambiguously processed by computers becomes more and more important. Two acknowledged fields in this evolving scientific area of Knowledge Representation are Description Logics (DL) and Formal Concept Analysis (FCA). While DL concentrates on characterizing domains via logical statements and inferring knowledge from these characterizations, FCA builds conceptual hierarchies on the basis of present data. This work introduces Relational Exploration, a method for acquiring complete relational knowledge about a domain of interest by successively consulting a domain expert without ever asking redundant questions. This is achieved by combining DL and FCA: DL formalisms are used for defining FCA attributes while FCA exploration techniques are deployed to obtain or refine DL knowledge specifications.
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Glodeanu, Cynthia Vera. "Conceptual Factors and Fuzzy Data." Doctoral thesis, Saechsische Landesbibliothek- Staats- und Universitaetsbibliothek Dresden, 2013. http://nbn-resolving.de/urn:nbn:de:bsz:14-qucosa-103775.
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With the growing number of large data sets, the necessity of complexity reduction applies today more than ever before. Moreover, some data may also be vague or uncertain. Thus, whenever we have an instrument for data analysis, the questions of how to apply complexity reduction methods and how to treat fuzzy data arise rather naturally. In this thesis, we discuss these issues for the very successful data analysis tool Formal Concept Analysis. In fact, we propose different methods for complexity reduction based on qualitative analyses, and we elaborate on various methods for handling fuzzy data. These two topics split the thesis into two parts. Data reduction is mainly dealt with in the first part of the thesis, whereas we focus on fuzzy data in the second part. Although each chapter may be read almost on its own, each one builds on and uses results from its predecessors. The main crosslink between the chapters is given by the reduction methods and fuzzy data. In particular, we will also discuss complexity reduction methods for fuzzy data, combining the two issues that motivate this thesisKomplexitätsreduktion ist eines der wichtigsten Verfahren in der Datenanalyse. Mit ständig wachsenden Datensätzen gilt dies heute mehr denn je. In vielen Gebieten stößt man zudem auf vage und ungewisse Daten. Wann immer man ein Instrument zur Datenanalyse hat, stellen sich daher die folgenden zwei Fragen auf eine natürliche Weise: Wie kann man im Rahmen der Analyse die Variablenanzahl verkleinern, und wie kann man Fuzzy-Daten bearbeiten? In dieser Arbeit versuchen wir die eben genannten Fragen für die Formale Begriffsanalyse zu beantworten. Genauer gesagt, erarbeiten wir verschiedene Methoden zur Komplexitätsreduktion qualitativer Daten und entwickeln diverse Verfahren für die Bearbeitung von Fuzzy-Datensätzen. Basierend auf diesen beiden Themen gliedert sich die Arbeit in zwei Teile. Im ersten Teil liegt der Schwerpunkt auf der Komplexitätsreduktion, während sich der zweite Teil der Verarbeitung von Fuzzy-Daten widmet. Die verschiedenen Kapitel sind dabei durch die beiden Themen verbunden. So werden insbesondere auch Methoden für die Komplexitätsreduktion von Fuzzy-Datensätzen entwickelt
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Kandasamy, Meenakshi. "Approaches to Creating Fuzzy Concept Lattices and an Application to Bioinformatics Annotations." Miami University / OhioLINK, 2010. http://rave.ohiolink.edu/etdc/view?acc_num=miami1293821656.
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Chow, Lai-kit, and 周禮傑. "Incorporating fuzzy membership functions and gap analysis concept intoperformance evaluation of engineering consultants: Hong Kong study." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2005. http://hub.hku.hk/bib/B32003699.
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Chow, Lai-kit. "Incorporating fuzzy membership functions and gap analysis concept into performance evaluation of engineering consultants Hong Kong study /." Click to view the E-thesis via HKUTO, 2005. http://sunzi.lib.hku.hk/hkuto/record/B32003699.
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Azzeh, Mohammad Y. A. "Analogy-based software project effort estimation : contributions to projects similarity measurement, attribute selection and attribute weighting algorithms for analogy-based effort estimation." Thesis, University of Bradford, 2010. http://hdl.handle.net/10454/4442.
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Software effort estimation by analogy is a viable alternative method to other estimation techniques, and in many cases, researchers found it outperformed other estimation methods in terms of accuracy and practitioners' acceptance. However, the overall performance of analogy based estimation depends on two major factors: similarity measure and attribute selection & weighting. Current similarity measures such as nearest neighborhood techniques have been criticized that have some inadequacies related to attributes relevancy, noise and uncertainty in addition to the problem of using categorical attributes. This research focuses on improving the efficiency and flexibility of analogy-based estimation to overcome the abovementioned inadequacies. Particularly, this thesis proposes two new approaches to model and handle uncertainty in similarity measurement method and most importantly to reflect the structure of dataset on similarity measurement using Fuzzy modeling based Fuzzy C-means algorithm. The first proposed approach called Fuzzy Grey Relational Analysis method employs combined techniques of Fuzzy set theory and Grey Relational Analysis to improve local and global similarity measure and tolerate imprecision associated with using different data types (Continuous and Categorical). The second proposed approach presents the use of Fuzzy numbers and its concepts to develop a practical yet efficient approach to support analogy-based systems especially at early phase of software development. Specifically, we propose a new similarity measure and adaptation technique based on Fuzzy numbers. We also propose a new attribute subset selection algorithm and attribute weighting technique based on the hypothesis of analogy-based estimation that assumes projects that are similar in terms of attribute value are also similar in terms of effort values, using row-wise Kendall rank correlation between similarity matrix based project effort values and similarity matrix based project attribute values. A literature review of related software engineering studies revealed that the existing attribute selection techniques (such as brute-force, heuristic algorithms) are restricted to the choice of performance indicators such as (Mean of Magnitude Relative Error and Prediction Performance Indicator) and computationally far more intensive. The proposed algorithms provide sound statistical basis and justification for their procedures. The performance figures of the proposed approaches have been evaluated using real industrial datasets. Results and conclusions from a series of comparative studies with conventional estimation by analogy approach using the available datasets are presented. The studies were also carried out to statistically investigate the significant differences between predictions generated by our approaches and those generated by the most popular techniques such as: conventional analogy estimation, neural network and stepwise regression. The results and conclusions indicate that the two proposed approaches have potential to deliver comparable, if not better, accuracy than the compared techniques. The results also found that Grey Relational Analysis tolerates the uncertainty associated with using different data types. As well as the original contributions within the thesis, a number of directions for further research are presented. Most chapters in this thesis have been disseminated in international journals and highly refereed conference proceedings.
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Blake, Gatto Sharon Elizabeth. "MAnanA: A Generalized Heuristic Scoring Approach for Concept Map Analysis as Applied to Cybersecurity Education." ScholarWorks@UNO, 2018. https://scholarworks.uno.edu/td/2526.
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Concept Maps (CMs) are considered a well-known pedagogy technique in creating curriculum, educating, teaching, and learning. Determining comprehension of concepts result from comparisons of candidate CMs against a master CM, and evaluate "goodness". Past techniques for comparing CMs have revolved around the creation of a subjective rubric. We propose a novel CM scoring scheme called MAnanA based on a Fuzzy Similarity Scaling (FSS) score to vastly remove the subjectivity of the rubrics in the process of grading a CM. We evaluate our framework against a predefined rubric and test it with CM data collected from the Introduction to Computer Security course at the University of New Orleans (UNO), and found that the scores obtained via MAnanA captured the trend that we observed from the rubric via peak matching. Based on our evaluation, we believe that our framework can be used to objectify CM analysis.
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Ostvik-de, Wilde Marte Erin. "Building Self-Esteem, Self-Concept, and Positive Peer Relations in Urban School Children: An Analysis of an Empowerment Program for Preadolescent Girls." Columbus, Ohio : Ohio State University, 2008. http://rave.ohiolink.edu/etdc/view?acc%5Fnum=osu1211943127.
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Mimouni, Nada. "Interrogation d'un réseau sémantique de documents : l'intertextualité dans l'accès à l'information juridique." Thesis, Sorbonne Paris Cité, 2015. http://www.theses.fr/2015USPCD084/document.
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Une collection documentaire est généralement représentée comme un ensemble de documents mais cette modélisation ne permet pas de rendre compte des relations intertextuelles et du contexte d’interprétation d’un document. Le modèle documentaire classique trouve ses limites dans les domaines spécialisés où les besoins d’accès à l’information correspondent à des usages spécifiques et où les documents sont liés par de nombreux types de relations. Ce travail de thèse propose deux modèles permettant de prendre en compte cette complexité des collections documentaire dans les outils d’accès à l’information. Le premier modèle est basée sur l’analyse formelle et relationnelle de concepts, le deuxième est basée sur les technologies du web sémantique. Appliquées sur des objets documentaires ces modèles permettent de représenter et d’interroger de manière unifiée les descripteurs de contenu des documents et les relations intertextuelles qu’ils entretiennentA collection of documents is generally represented as a set of documents but this simple representation does not take into account cross references between documents, which often defines their context of interpretation. This standard document model is less adapted for specific professional uses in specialized domains in which documents are related by many various references and the access tools need to consider this complexity. We propose two models based onformal and relational concept analysis and on semantic web techniques. Applied on documentary objects, these two models represent and query in a unified way documents content descriptors and documents relations
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Toth, Zsofia. "Attractiveness in business-to-business markets : conceptual development and empirical investigation." Thesis, University of Manchester, 2015. https://www.research.manchester.ac.uk/portal/en/theses/attractiveness-in-businesstobusiness-marketsconceptual-development-and-empirical-investigation(856a6f4a-1dfa-4256-8668-24dfc3b6bbd7).html.
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Attractiveness matters in business markets, because firms do not dedicate resources equally to all partners. Instead they invest more resources in partners with higher relational attractiveness. Firms need to become attractive in order to gain access to more resources or to be able to work with more skilled or reputable partners. This dissertation studies the construct of relational attractiveness of the customer (RAC), defined as the attractiveness of a business relationship with a particular customer in the eyes of the supplier. The research also investigates corporate online references (COR), because gaining powerful referrals is one of the driving forces behind creating attractiveness in business markets. The study is a three-stage research project drawing on an empirical investigation comprising two focus groups, 79 interviews, a survey of 107 suppliers and online referral data from 1002 companies. These studies investigate the conditions and configurations leading to high or low relational attractiveness, and the motivational conditions and structure of a specific corporate online referral network. Bearing in mind that attractiveness exists in the eyes of the beholder, Study I resolves the previously unclarified problem of how attractiveness can be achieved in different ways. Social Exchange Theory helps to identify conditions of RAC: Trust, Dependency, Financial, Non-Financial Rewards and Costs. In Study II conditions of Trust and Dependency are further developed into Relational Fit and the Comparison Level of Alternatives that address the mutuality and network perspectives of relationship development. The time perspective is introduced to the configurational analysis of RAC through the Maturity condition. As it is revealed in Study I and II, Nonfinancial Rewards are important in creating attractiveness and one of their essential forms is referrals that are addressed in more detail in Study III. This PhD research takes a configurational approach to attractiveness and explores different causal recipes in order to reach the same outcome. In order to investigate the relational complexity of attractiveness, fuzzy set Qualitative Comparative Analysis (fsQCA) is applied throughout the three studies combined with some other methods, such as content analysis and Social Network Analysis (SNA). QCA is a data analytic strategy that combines within-case analysis and formalised cross-case studies in order to identify multiple configurations leading to the same outcome. Hence, QCA deals more efficiently with the equifinality of complex business problems compared with traditional data analysis methods. Equifinality means that there are various ways in the causal system of achieving the desired outcome. QCA is sufficient in handling methodological challenges such as multi-causality (an outcome of interest rarely has a single cause), interrelatedness (causes are usually not independent of one another) and asymmetry (a specific cause may have different effects on the outcome depending on the context). By challenging existing knowledge, the results show that there is no one best way to achieve relational attractiveness. It is achievable even if Trust and Financial Rewards are not present. Very high RAC was typically achieved in less mature relationships. During the initiation of referral relationships in the case of COR, the expected increase in the initiators` attractiveness in the eyes of potential future partners also plays a vital role. The generalizability of the findings has some limitations, especially regarding the qualitative study where the results are appropriate to falsify some theories (for example, the primary importance of Financial Rewards) but their impact is more related to theoretical development than to statistical generalizability.
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Ayouni, Sarra. "Etude et Extraction de règles graduelles floues : définition d'algorithmes efficaces." Thesis, Montpellier 2, 2012. http://www.theses.fr/2012MON20015/document.
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L'Extraction de connaissances dans les bases de données est un processus qui vise à extraire un ensemble réduit de connaissances à fortes valeurs ajoutées à partir d'un grand volume de données. La fouille de données, l'une des étapes de ce processus, regroupe un certain nombre de taches, telles que : le clustering, la classification, l'extraction de règles d'associations, etc.La problématique d'extraction de règles d'association nécessite l'étape d'extraction de motifs fréquents. Nous distinguons plusieurs catégories de motifs : les motifs classiques, les motifs flous, les motifs graduels, les motifs séquentiels. Ces motifs diffèrent selon le type de données à partir desquelles l'extraction est faite et selon le type de corrélation qu'ils présentent.Les travaux de cette thèse s'inscrivent dans le contexte d'extraction de motifs graduels, flous et clos. En effet, nous définissons de nouveaux systèmes de clôture de la connexion de Galois relatifs, respectivement, aux motifs flous et graduels. Ainsi, nous proposons des algorithmes d'extraction d'un ensemble réduit pour les motifs graduels et les motifs flous.Nous proposons également deux approches d'extraction de motifs graduels flous, ceci en passant par la génération automatique des fonctions d'appartenance des attributs.En se basant sur les motifs flous clos et graduels clos, nous définissons des bases génériques de toutes les règles d'association graduelles et floues. Nous proposons également un système d'inférence complet et valide de toutes les règles à partir de ces basesKnowledge discovery in databases is a process aiming at extracting a reduced set of valuable knowledge from a huge amount of data. Data mining, one step of this process, includes a number of tasks, such as clustering, classification, of association rules mining, etc.The problem of mining association rules requires the step of frequent patterns extraction. We distinguish several categories of frequent patterns: classical patterns, fuzzy patterns, gradual patterns, sequential patterns, etc. All these patterns differ on the type of the data from which the extraction is done and the type of the relationship that represent.In this thesis, we particularly contribute with the proposal of fuzzy and gradual patterns extraction method.Indeed, we define new systems of closure of the Galois connection for, respectively, fuzzy and gradual patterns. Thus, we propose algorithms for extracting a reduced set of fuzzy and gradual patterns.We also propose two approaches for automatically defining fuzzy modalities that allow obtaining relevant fuzzy gradual patterns.Based on fuzzy closed and gradual closed patterns, we define generic bases of fuzzy and gradual association rules. We thus propose a complet and valid inference system to derive all redundant fuzzy and gradual association rules
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Lidhamullage, Dhon Charles Shashikala Subhashini. "Integration of multiple features and deep learning for opinion classification." Thesis, Queensland University of Technology, 2022. https://eprints.qut.edu.au/228567/1/Shashikala%20Subhashini_Lidhamullage%20Dhon%20Charles_Thesis.pdf.
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Opinion classification is used to classify and analyze the opinions in text-based product and service reviews. However, due to the uncertainty of opinion data, it is difficult to gain satisfactory classification accuracy using existing machine learning algorithms. Therefore, how to deal with uncertainty in opinions to improve the performance of machine learning is a challenge. This thesis develops a three-way decision-making framework to support two-stage decision making. It first divides opinions into positive, negative, and boundary regions using fuzzy concepts, and then classifies the boundaries again using semantic features and deep learning. It provides a promising method for opinion classification.
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Койбічук, Віталія Василівна, Виталия Васильевна Койбичук, Vitalia Vasylivna Кoybichuk, and Л. М. Малярець. "Концепція нечіткого регресійного аналізу конкурентоспроможності банку." Thesis, Середняк Т.К, 2015. http://essuir.sumdu.edu.ua/handle/123456789/59931.
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Викладена концепція описового моделювання конкурентоспроможності банку на основі нечіткого регресійного аналізу. В пропонованій нечіткій ба-гатофакторній лінійній регресійній моделі розглядається критерій мінімізації нечіткості для оцінки нечітких параметрів математичної моделі.The conception of descriptive modeling competitiveness bank based on fuzzy regression analysis. In the proposed fuzzy multivariate linear regression model is considered a criterion for minimizing the fuzziness of fuzzy evaluation parameters of the mathematical model.
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Dao, Ngoc Bich. "Réduction de dimension de sac de mots visuels grâce à l’analyse formelle de concepts." Thesis, La Rochelle, 2017. http://www.theses.fr/2017LAROS010/document.
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La réduction des informations redondantes et/ou non-pertinentes dans la description de données est une étape importante dans plusieurs domaines scientifiques comme les statistiques, la vision par ordinateur, la fouille de données ou l’apprentissage automatique. Dans ce manuscrit, nous abordons la réduction de la taille des signatures des images par une méthode issue de l’Analyse Formelle de Concepts (AFC), qui repose sur la structure du treillis des concepts et la théorie des treillis. Les modèles de sac de mots visuels consistent à décrire une image sous forme d’un ensemble de mots visuels obtenus par clustering. La réduction de la taille des signatures des images consiste donc à sélectionner certains de ces mots visuels. Dans cette thèse, nous proposons deux algorithmes de sélection d’attributs (mots visuels) qui sont utilisables pour l’apprentissage supervisé ou non. Le premier algorithme, RedAttSansPerte, ne retient que les attributs qui correspondent aux irréductibles du treillis. En effet, le théorème fondamental de la théorie des treillis garantit que la structure du treillis des concepts est maintenue en ne conservant que les irréductibles. Notre algorithme utilise un graphe d’attributs, le graphe de précédence, où deux attributs sont en relation lorsque les ensembles d’objets à qui ils appartiennent sont inclus l’un dans l’autre. Nous montrons par des expérimentations que la réduction par l’algorithme RedAttsSansPerte permet de diminuer le nombre d’attributs tout en conservant de bonnes performances de classification. Le deuxième algorithme, RedAttsFloue, est une extension de l’algorithme RedAttsSansPerte. Il repose sur une version approximative du graphe de précédence. Il s’agit de supprimer les attributs selon le même principe que l’algorithme précédent, mais en utilisant ce graphe flou. Un seuil de flexibilité élevé du graphe flou entraîne mécaniquement une perte d’information et de ce fait une baisse de performance de la classification. Nous montrons par des expérimentations que la réduction par l’algorithme RedAttsFloue permet de diminuer davantage l’ensemble des attributs sans diminuer de manière significative les performances de classificationIn several scientific fields such as statistics, computer vision and machine learning, redundant and/or irrelevant information reduction in the data description (dimension reduction) is an important step. This process contains two different categories : feature extraction and feature selection, of which feature selection in unsupervised learning is hitherto an open question. In this manuscript, we discussed about feature selection on image datasets using the Formal Concept Analysis (FCA), with focus on lattice structure and lattice theory. The images in a dataset were described as a set of visual words by the bag of visual words model. Two algorithms were proposed in this thesis to select relevant features and they can be used in both unsupervised learning and supervised learning. The first algorithm was the RedAttSansPerte, which based on lattice structure and lattice theory, to ensure its ability to remove redundant features using the precedence graph. The formal definition of precedence graph was given in this thesis. We also demonstrated their properties and the relationship between this graph and the AC-poset. Results from experiments indicated that the RedAttsSansPerte algorithm reduced the size of feature set while maintaining their performance against the evaluation by classification. Secondly, the RedAttsFloue algorithm, an extension of the RedAttsSansPerte algorithm, was also proposed. This extension used the fuzzy precedence graph. The formal definition and the properties of this graph were demonstrated in this manuscript. The RedAttsFloue algorithm removed redundant and irrelevant features while retaining relevant information according to the flexibility threshold of the fuzzy precedence graph. The quality of relevant information was evaluated by the classification. The RedAttsFloue algorithm is suggested to be more robust than the RedAttsSansPerte algorithm in terms of reduction
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Wajnberg, Mickaël. "Analyse relationnelle de concepts : une méthode polyvalente pour l'extraction de connaissances." Electronic Thesis or Diss., Université de Lorraine, 2020. http://www.theses.fr/2020LORR0136.
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À une époque où les données, souvent interprétées comme une «réalité terrain»,sont produites dans des quantités gargantuesques, un besoin de compréhension et d’interprétation de ces données se développe en parallèle. Les jeux de données étant maintenant principalement relationnels, il convient de développer des méthodes qui permettent d’extraire de l’information pertinente décrivant à la fois les objets et les relations entre eux. Les règles d’association, adjointes des mesures de confiance et de support, décrivent les co-occurences entre les caractéristiques des objets et permettent d’exprimer et d’évaluer de manière explicite l’information contenue dans un jeu de données. Dans cette thèse, on présente et développe l’analyse relationnelle de concepts pour extraire des règles traduisant tant les caractéristiques propres d’un ensemble d’objets que les liens avec d’autres ensembles. Une première partie développe la théorie mathématique de la méthode, alors que la seconde partie propose trois cas d’application pour étayer l’intérêt d’un tel développement. Les études sont réalisées dans des domaines variés montrant ainsi la polyvalence de la méthode : un premier cas traite l’analyse d’erreur en production industrielle métallurgique, un second cas est réalisé en psycholinguistique pour l’analyse de dictionnaires et un dernier cas montre les possibilités de la méthode en ingénierie de connaissanceAt a time where data, often interpreted as "ground truth", are produced in gigantic quantities, a need for understanding and interpretability emerges in parallel. Dataset are nowadays mainly relational, therefore developping methods that allows relevant information extraction describing both objects and relation among them is a necessity. Association rules, along with their support and confidence metrics, describe co-occurrences of object features, hence explicitly express and evaluate any information contained in a dataset. In this thesis, we present and develop the relational concept analysis approach to extract the association rules that translate objects proper features along with the links with sets of objects. A first part present the mathematical part of the method, while a second part highlights three case studies to assess the pertinence of such a development. Case studies cover various domains to demonstrate the method polyvalence: the first case deals with error analysis in industrial production, the second covers psycholinguistics for dictionary analysis and the last one shows the method application in knowledge engineering
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Randyanto, Yonathan, and 黄義亮. "Concept Representation and Database Structures in Intuitionistic Fuzzy Social Relational Networks." Thesis, 2014. http://ndltd.ncl.edu.tw/handle/62016948622980924831.
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碩士國立臺灣科技大學
資訊工程系
102
Recently, social networks have become a major trend of computing and social paradigms. We realize that intuitionistic fuzzy concepts have a lot of potentials to be applied in the field of social networks. Therefore, in this thesis, we propose a novel similarity measure between intuitionistic fuzzy sets and intuitionistic fuzzy social graphs to model and analyze intuitionistic fuzzy social relational networks model which contain positive relationships and negative relationships between actors. We also show some properties of intuitionistic fuzzy relations between vertices in intuitionistic fuzzy social graphs. Then, we propose the concept of the strength of connectedness between vertices, having at most k edges between them, in an intuitionistic fuzzy social graph and define the intuitionistic fuzzy level-cut of the strength of connectedness between vertices. In order to measure the importance of a vertex in an intuitionistic fuzzy social graph, we propose the concept of the degree of centrality of a vertex in intuitionistic fuzzy social graphs. Then, we propose the concept of intuitionistic fuzzy clusters by the paradigm of computing with words. Finally, we propose queries processing techniques in an intuitionistic fuzzy social relational network. The proposed intuitionistic fuzzy social relational network model can overcome the drawback of Yager’s fuzzy social relational network model.
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黃大偉. "Event Tree Analysis Using Fuzzy Concept." Thesis, 1997. http://ndltd.ncl.edu.tw/handle/11517306333510215915.
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碩士國立清華大學
工業工程研究所
85
Event tree analysis (ETA) method is a straightforward and simple approach for risk assessment. It can be used to identify various sequences and their causes, and also to give the analyst the clear picture about which top event dominates the safety of the system. The traditional ETA uses a single probability to represent each top event. However, it is unreasonable to evaluate the occurrence of an event by using a crisp value without considering the inherent uncertainty and imprecision a state has. Since fuzzy set theory provides a framework for dealing with this kind of phenomena, this tool is used in this study. The main purpose of this study is to make an effort in constructing an easy methodology to evaluate the human error and integrates it into ETA by using fuzzy concept. In addition, a systematic FETA algorithm is developed to evaluate the risk of a large scale system. A practical example of an ATWS event in a nuclear power plant is used to demonstrate the procedure. The fuzzy outcomes will be defuzzified by using the total integral value in terms of the degree of optimism the decision maker has. At last, more information about the importance and uncertainty of top events will be provided by using the two indices.
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JIANG, ZIH-HUA, and 江姿樺. "Novel Methods of Fuzzy Query Operation and Concept Relational Degree of Document Retrieval." Thesis, 2017. http://ndltd.ncl.edu.tw/handle/jw4x84.
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碩士國立聯合大學
資訊管理學系碩士班
105
This thesis firstly discusses the problems of existing AND/OR operators in fuzzy document retrieval, and proposes novel AND/OR query operators based on P-norm operator to handle these problems. We also use some examples to compare the proposed AND/OR operators with existing methods. Then, some articles pointed out that it is an important process to obtain the degree of correlation between concepts for constructing the multi-relational fuzzy concept networks in document retrieval. Therefore, we propose a new method to calculate the degree of correlation between concepts, and use some examples to compare the proposed method with existing methods. Finally, we summarize the new methods proposed in this thesis.
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Peng, Jin-De, and 彭晉德. "Apply Document Processing Techniques to Improve Fuzzy Formal Concept Analysis Concept Quality." Thesis, 2013. http://ndltd.ncl.edu.tw/handle/13267447827823741877.
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碩士國立雲林科技大學
資訊管理系碩士班
101
Traditional Formal Concept Analysis (FCA) has been blamed for its drawback that fails to deal with uncertain information; furthermore, its performance to administer and searching deteriorated while coping with a large amount of documents and particularly in wider domains. To deal with this drawback, this study employed Fuzzy Theory into FCA and used Event Detection Clustering Technique based on the experimental dataset from Yahoo! News. We extracted news features through syntax rules and assigned normalized TF-IDF as membership grade. Then, event detection clustering was carried out to decrease the complexity of document set, enhance quality of searching and shorten the duration of processing. In comparison with traditional FCA, the results showed that our proposed method, assessing the quality of concept lattice through fuzzy rate, had higher fuzzy rate and the quality also increased as α-cut was higher. Furthermore, we are able to find an appropriate α-cut to build more precise concept lattice through users’ satisfaction. Experimental results showed that users indicate that the concept expressed the news contents best as the α-cut was 0.06 in this study.
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Hsu, Ming-Tse, and 徐銘澤. "Grey Relational Analysis for Improving Unacceptable Consistency of Fuzzy Pairwise Comparison Matrices." Thesis, 2010. http://ndltd.ncl.edu.tw/handle/61638733787098840756.
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碩士中原大學
企業管理研究所
98
Under uncertainty and multi-attribute, Analytic Hierarchy Process (AHP) is the applied decision-making tool. AHP uses the pairwise comparison among widely aspects, criteria, and alternatives to get the relative weight, and finds the best aspect, criterion, or alternative. In the cause of avoiding resulting inconsistency, all of the pairwise comparison matrixes have to test their consistency. However, in the practices, the consistency is hard to achieve. Because when the orders of pairwise comparison matrixes is larger and larger, the inconsistency is easier to occur. So, not only how to let the all questionnaires can be utilized adequately, but how to appropriately improve the quality of pairwise comparison matrix to let its consistency can be less than 0.1 is worth discussing issue. Due to fuzzy sets can deal with the uncertainty of subjective cognition and respondents’ perception, in addition, it has more flexibility on linguistic than the Saaty scale, so, for the AHP and ANP (Analytic Network Process), the fuzzy pairwise comparison matrix that improves the inconsistency is the important research issue. The main purpose of our study is to take the Grey Relational Analysis (GRA) as the base to built improvement model of fuzzy matrix of unacceptable consistency. In the past, some scholars also bring up other methods to improve the consistency, but they just take some simple examples to explain, not a large number of experiment examples to evidence, so, it’s difficult to know the effectiveness. We take seven methods which can improve consistency to compare with the result of GRA to observe that which method is the best for keeping the information of original matrix, and as the standard of performance evaluation among methods. Our results are: (1) The comparative sequences are the most similar, but their Grey Relational Grades (GRG) are not necessarily relatively the most. So, we find the best alternative and the ranking GRA preferred; (2) When the orders is more, the ranking is closer for every inconsistency interval. On the other hand, when GRA is the low inconsistency, it has the most positive correlation for selecting the best alternative, and vice versa; (3) Compared to other methods, when orders is three or four, it can find the best alternative, and has the most correlation for the ranking of GRA. By the results, our study finds the relationship between the best comparative sequences and the alternative evaluation of GRA.
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Chang, Fei Bin, and 張斐斌. "Item relational structure analysis of the fraction concept for the fourth graders." Thesis, 2011. http://ndltd.ncl.edu.tw/handle/81032152631056165254.
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碩士國立臺中教育大學
數學教育學系在職進修教學碩士學位班
99
The purpose of this study is to confer the development of fraction concepts in fourth grade. According to analyze the students’ performance of fraction concepts. To understand the development of fraction concepts for fourth graders. Based on the purpose, the research chooses 146 students of a Taichung elementary schools as objects of this study. The research edit fraction examination, adopts item relational structure analysis concept, and analyze the connection of examination. The fraction concepts of analysis are : equivalent division , unit fraction, unit quantity, simple fraction, proper fraction, improper fraction, mixed fraction. The results of this study are as follows: 1.Students have to understand equivalent division concept of continuous quantity. Then to understand equivalent division concept of divergent quantity. 2.Students have to understand the content’s unit quantity concept of single or multiple ones. Then expand to different unit quantity or unit quantity concept of unknown unit quantity. 3.Students have to develop proper fraction concept which not integer and which is single of content. Then expand to which is multiple of content. 4.Students have to develop integer division concept of mixed fraction. Then expand to integer division concept of improper fraction which includes unit quantity concept. 5.Students have to understand unit quantity concept of continuous quantity and content is multiple. Then can manage simple fraction concept of continuous quantity and content is multiple.
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Lin, Shin-Yang, and 林欣洋. "Knowledge Exploration in Drug Interaction using Fuzzy Formal Concept Analysis." Thesis, 2007. http://ndltd.ncl.edu.tw/handle/43035149416098183090.
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碩士國立成功大學
資訊管理研究所
95
The improvements in pharmaceutics, accompanied by medicinal and technological advances, have expanded the diversity of pharmaceuticals to a great extent, turning the world of pharmacology into a complex web of drugs, their interactions, and most important of all, their effects on patients. The increasing number of existent pharmaceuticals inevitably complicates the interactions between them, revealing the importance of their thorough understanding in order to prevent possible pathogenic symptoms. This is emphasized by the seriousness of drug misuse and the related consequences. This paper utilizes Fuzzy Formal Concept Analysis in the process of medicinal data analysis to uncover the ongoing connections between the formal concepts and the strengths of these relationships. The tacit knowledge extracted helps experts have a better insight of the pharmaceuticals and the possible drug interactions, consequently improving their usage in terms of effectiveness and reducing mistreatment.
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Kung, Tien-Kuan, and 龔天冠. "Short-term Load Forecasting Using Grey Relational Analysis and Fuzzy Adaptive Resonance Theory." Thesis, 2013. http://ndltd.ncl.edu.tw/handle/6k6qna.
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碩士國立臺北科技大學
自動化科技研究所
101
For electric utility, accurate load forecasting can avoid the crisis of restricting the use of electricity and the wasting of resources, and can enhance the stability and safety of power system operation. The power supply of substations changes daily, and the load is unfixed, however, there is no algorithm having optimal predictive validity in all situations. Therefore, this thesis proposes the grey fuzzy adaptive resonance network as the load forecasting model. The grey fuzzy adaptive resonance network has fast learning, the intrinsic clustering rule is learned in the case of low data volume and the correlation grade of data is measured by grey relational analysis. The grey relational grade and the cross-validation method optimized vigilance value are used for resonance test. The plasticity and stability of network are adjusted to reach high prediction accuracy. Afterwards, this study will discuss the effectiveness of three algorithms, the predictive model proposed, the fuzzy adaptive resonance network and fuzzy time series forecasting model in the experimental analysis, so as to find out the most suitable method for short-term load forecasting. The experimental process is divided into two parts in this thesis. There are five groups of experimental samples in the first part of experiment. The difference and quality are discussed according to the forecast results of the five groups of experimental samples in three predictive models. The second part of experiment uses the daily capacity of a substation equipped with four main transformers in the north in summer as actual forecast. Finally, according to the actual load forecasting, the root mean squared error is 0.2448, and the mean absolute percentage error is 0.58%. The results prove that the predictive model proposed in this thesis actually has good prediction efficiency in short-term load forecasting.
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Wu, Chun-Hsin, and 吳純欣. "Apply the polytomous item relational structure and fuzzy clustering to analyze the concept of algebra for Elementary school students." Thesis, 2011. http://ndltd.ncl.edu.tw/handle/80752013543428647766.
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碩士國立臺中教育大學
數學教育學系在職進修教學碩士學位班
99
The purpose of this study is to integrate fuzzy clustering and polytomous item relational structure on algebra concept for pupils. The subjects include 709 and 705 students from fourth graders and fifth graders respectively. The assessment tool is a self-designed algebraic concepts test according to the mathematics content in Grade 1-9 Curriculum. Firstly, fuzzy clustering is adopted to classify all students into two groups based on similarity coefficient. Secondly, the researcher adopts PIRS (Polytomous Item Relational Structure) to analyze the knowledge structures of students respective to these two groups. These knowledge structure graphs will reveal the cognitive information of students. Through the procedures of the analysis, the following conclusions were found. 1. The overall student's algebra concept provides no ordering relationship and it is hard to help remedial instruction. 2. According to the results of clustering, each cluster reveals its specific item difficulty, item ordering and those concepts of mastery and difficulty. 3. Each cluster has its own concept structure graph. Therefore, there should be different teaching strategy and remedial instruction for each cluster. As shown in the results, the method of this study could help teacher understand concept structures of students. This information could be the references for remedial instruction and curriculum design. Finally, some recommendations and suggestions for future research are discussed. Keyword: algebra, fuzzy clustering, polytomous item relational structure.
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Shiu, Chih-Yu, and 許志宇. "Applications of Quality Function Deployment, Fuzzy Theory and Grey Relational Analysis in Green Designs." Thesis, 2005. http://ndltd.ncl.edu.tw/handle/72024745543079286687.
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碩士國立高雄應用科技大學
工業工程與管理系碩士班
93
In this research, a method integrated with the concepts and techniques of quality function deployment (QFD) and green lif cycle design (GLCD) is proposed in analyzing the necessary quality characteristics of single use camera in the design process for (qualified) quality management. The proposed method transforms the process design, usage, package, and abortion in different stages of manufacturing design into product’s design characteristics applying techniques form QFD, fuzzy theory, and gray relational analysis (GRA) to insight the voices of customers. Questionnaire is used to get the necessary data for empirical study. The empirical results showed that consumers would pay more attention to the attributes of “reuse”, “nightly use”, “anti-pollution”, “firmness”, “film’s sense of touch”, “convenience”, and “price”, than other product attributes considered. To implement the concepts of green product lifecycle for manufacture, these customers’ preferred attributes were converted to equivalent engineering parameters: “material”, “sensitization”, “retrial”, “battery”, and “reuse” using QFD, fuzzy theory, and GRA. Further, the Spearman rank R is used to test the correlation between two variables measured on at least an ordinal (rank order) scale. The test showed that there is no significant difference among the rank order of the manufacturing parameters using QFD, fuzzy theory, and GRA. Based on the empirical finding, suggestions and recommendations are offered to product manufacturers.
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Li, Chia-Yuan, and 李嘉淵. "Apply Evolutional Neural Network, Gray Relational Analysis and Fuzzy-Neural in Real Estate Appraisement." Thesis, 2005. http://ndltd.ncl.edu.tw/handle/8e6amh.
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碩士朝陽科技大學
財務金融系碩士班
93
Real estate is one of the most useful financial instruments and can be applied to the purposes of the settlement of claims, financing, auction and taxing. To make most use of this financial tool requires appraising the assets accurately. In general, the comparative method of markets is a common approach for the evaluation of real estate. However, the selection of variables and related weights of this method relies on the assessor’s subjective judgment and the justice and rationality of results are disputed. Appraisement plays a very important role in the real estate market. Appropriate appraisement can provide the consumers and investors sufficient trade information and also support the planning of the government real estate police. As the real estate market in Taiwan is not a perfect market, the consumers are prone to suffer loss due to the lack of correct appraisement information. As a result, the precision and circulation of the appraisement information is critical for the real estate market. Without the assistance of sophisticated appraisement techniques, real estate appraiser’s results can not convince the consumers. This study integrated evolutional neural network, gray relational and neural-fuzzy analysis approaches to construct an intelligent system and provide an objective view for the appraiser. The gray relational analysis is applied to extract important variables which are the inputs for the neural network during the empirical test. The structure of prototype system built in this study will provide a reference and basis for the development of advance real estate appraisement system in the future.
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Chen, Hsieh Hui, and 謝惠珍. "The Study of Selection Optimization of Middle Managers by Grey Relational Analysis and Fuzzy Theory." Thesis, 2008. http://ndltd.ncl.edu.tw/handle/90307497885419490120.
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碩士國防管理學院
資源管理研究所
96
As a response to variations in international conditions, national strategies and the new generation troops, several organization reengineering methods have been developed in military during the few years. Moreover, there is facing towards a flat organizational structure, so that the reduced membership of the organization could be better than before. While the organization is passing through a rapid and full-scale change, it should be driven by the managers who possess professional knowledge, professional skill, diplomatic skill and conceptual skill to work out. Because of managers serve as coordinators and also as revelators of the organization, therefore the selection and judgment standards with managers must be stricter than the others. In this paper, we adopt factor analysis method to know what ability a manager in military should possess. As a result, we got five ability pointers including personality, relationship, execution, administration, and leadership to choose a manager in military. Until now, none of the units have a way to choose managers which could consider all dimensions. In order to solve the problem, we apply fuzzy set theory then set appraised pointer, which create the model of fuzzy multiple criteria decision making to score and judge. By applying the model will let the processes be more fair and reasonable to employ on the basis of competitive selection, as be the references of more enterprises to reserve the executives.
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Rudolph, Sebastian [Verfasser]. "Relational exploration : combining description logics and formal concept analysis for knowledge specification / von Sebastian Rudolph." 2006. http://d-nb.info/983709688/34.
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Cheng, HsuFeng, and 鄭旭峰. "The Study on “Information Security” News Retrieval by using Fuzzy Formal Concept Analysis." Thesis, 2013. http://ndltd.ncl.edu.tw/handle/73187591349099605567.
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碩士國防大學管理學院
資訊管理學系
101
In today's ever-expanding universe of knowledge, digital documentation to be a trend, online information is the main part of knowledge resources. Therefore, to cite the past valuable references and try to find out how to make the massive volume of data as a file, to categorize and search relevant information in an efficient way is the critical issue of current studies. Nowadays we can use index application in plenty websites, and the way of navigating based on “Keywords”, however in this way, it cannot be more efficient to search one certain topic during navigation. Besides, if the search engine establishes on “Subject-Specific”, the main category is made by manually- it might be time-consuming and strenuous to handle with such a plenty data information. Therefore, the main purpose of this study is to figure out what’s the automatic classify system in search application, to aim for improving effectiveness in knowledge representation and discovery. There are three main purposes of this study- first, to acquire specific terms as our foundation, combine Fuzzy Formal Concept Analysis (FFCA) method as analysis process to set up the ontology and the concept relationship automatically for the information security domain. Second, the news reporting states on the website of “Information Security” which is the main resource of training materials. Query Expansion is the main navigation method. Third, to construct the systemized query model on information security news, the system then can get some recommended contents and then expand the search results and increase the retrieval efficiency . The conclusion of this study is to validate the establish timing would be shorten by Ontology set on automatic searching system- it is superior to manual one. To construct domain ontology based on FFCA is beneficial than Formal Concept Analysis. Experimental results on “Information Security News Retrieval Systems” illustrate the most efficient way to expand all relevant contents for every user.
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Chang, CheChun, and 張哲郡. "Item ordering theory and relational structure analysis to apply fifth grade students factor and multiple concept." Thesis, 2011. http://ndltd.ncl.edu.tw/handle/82443408258061822067.
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碩士國立臺中教育大學
教育測驗統計研究所
99
The purpose of this study is to apply the ordering theory and item relational structure analysis, to learn fifth grade students "factor and multiple concept " of the structure and associated with the ordering theory of item relational structure analysis of the differences in how the results of their analysis ? beside to Touchstone for application and provide the educational field of the teachers. This study selected fifth grade students in Taichung city as the research object. With the preparation of technical papers, the establishment of the test factor and multiple research tools. Surveying pop star collected after the reaction. Use the ordering theory and item relational structure analysis and item ordering relational structure analysis. Draw with on the concept of lower structural relationship, research findings can be concluded as following: 1. OT results of the analysis with the IRS is not much difference, said the students the concept of factor and multiple structure, the structure of expert knowledge and no big difference. 2. OT with the IRS In comparison, on the order of rationality, OT better than the IRS, so the analysis in this section shows OT stringent than the IRS, there is more appropriate. 3. IORS analysis of the project on the relationship between the number of between OT and IRS, and the association with which repeat are highly consistent with the functional combination of the two.
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Weng, Jia Ling, and 翁佳麟. "The Job Oriented Heuristic Scheduling System for Job Shop Using Fuzzy Multi-objective Hybrid Grey Relational Analysis." Thesis, 2001. http://ndltd.ncl.edu.tw/handle/75569362559056255902.
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碩士國立臺北科技大學
生產系統工程與管理研究所
89
Scheduling is among the most important operation in production management. In the traditional seller’s market, scheduling emphasizes on the flow shop type, which specializes in high-volume, low-cost and high-utilization production. On the other hand, to match the needs of customers in the buyer’s market, scheduling focuses on the job shop type, which specializes in low-to-medium volume and resource-sharing production. Job shop scheduling problems become more complex under uncertain production environments due to the needs of quick response and closer due date, etc. Owing to the above reasons, researchers pay more attention to the study of job shop scheduling problems. The scheduling approaches of conventional Operation Research try to find the optimal solution under resource constraints. The optimal solution costs a lot of computational efforts and yet sometimes impossible to get. Heuristic approaches use fewer efforts to get sub-optimal or sometimes even optimal solutions. Hastings divides heuristics of scheduling problems into two categories, the operation oriented heuristics, OOH, and the job oriented heuristics, JOH. OOH finds the most suitable operation to be processed for the machine. JOH first determines the priorities for all jobs and then schedule their operation sequences for each machine. In general, job shop scheduling with many orders prefers JOH than OOH. Recent researches of JOH focus on scheduling of single objective. In this research, we propose a job shop scheduling system that integrates fuzzy multi-objective methods to consider both quantity and quality scheduling factors with Grey Relational Analysis that determines job priorities to effectively solve the scheduling problems with dynamic environment, uncertain situation, statistical fluctuations, dependent events, and conflict objectives. We used the VBA for Excel to conduct the scheduling system based on our research and tested 8 kinds of experiments with different jobs and machines. By testing statistical hypotheses, our method is superior on reducing processing time of jobs.
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Glodeanu, Cynthia Vera. "Conceptual Factors and Fuzzy Data." Doctoral thesis, 2012. https://tud.qucosa.de/id/qucosa%3A26470.
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With the growing number of large data sets, the necessity of complexity reduction applies today more than ever before. Moreover, some data may also be vague or uncertain. Thus, whenever we have an instrument for data analysis, the questions of how to apply complexity reduction methods and how to treat fuzzy data arise rather naturally. In this thesis, we discuss these issues for the very successful data analysis tool Formal Concept Analysis. In fact, we propose different methods for complexity reduction based on qualitative analyses, and we elaborate on various methods for handling fuzzy data. These two topics split the thesis into two parts. Data reduction is mainly dealt with in the first part of the thesis, whereas we focus on fuzzy data in the second part. Although each chapter may be read almost on its own, each one builds on and uses results from its predecessors. The main crosslink between the chapters is given by the reduction methods and fuzzy data. In particular, we will also discuss complexity reduction methods for fuzzy data, combining the two issues that motivate this thesis.Komplexitätsreduktion ist eines der wichtigsten Verfahren in der Datenanalyse. Mit ständig wachsenden Datensätzen gilt dies heute mehr denn je. In vielen Gebieten stößt man zudem auf vage und ungewisse Daten. Wann immer man ein Instrument zur Datenanalyse hat, stellen sich daher die folgenden zwei Fragen auf eine natürliche Weise: Wie kann man im Rahmen der Analyse die Variablenanzahl verkleinern, und wie kann man Fuzzy-Daten bearbeiten? In dieser Arbeit versuchen wir die eben genannten Fragen für die Formale Begriffsanalyse zu beantworten. Genauer gesagt, erarbeiten wir verschiedene Methoden zur Komplexitätsreduktion qualitativer Daten und entwickeln diverse Verfahren für die Bearbeitung von Fuzzy-Datensätzen. Basierend auf diesen beiden Themen gliedert sich die Arbeit in zwei Teile. Im ersten Teil liegt der Schwerpunkt auf der Komplexitätsreduktion, während sich der zweite Teil der Verarbeitung von Fuzzy-Daten widmet. Die verschiedenen Kapitel sind dabei durch die beiden Themen verbunden. So werden insbesondere auch Methoden für die Komplexitätsreduktion von Fuzzy-Datensätzen entwickelt.
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Chang, Wen-Li, and 張文莉. "On item relational structure analysis and the understanding of the 6th grade students in the concept of area." Thesis, 2009. http://ndltd.ncl.edu.tw/handle/60780565524476570847.
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碩士國立臺中教育大學
數學教育學系
97
The purpose of this study is to investigate the comprehension of the 6th grade students in the concept of area and to understand the knowledge structure of the 6th grade students in the concept of area by using Item Relational Structure Analysis. This study samples 302 6th grade students from six primary schools in Changhua County to have a hand-write test and interviews 48 students of them to understand students’ common errors and problem-solving strategies in area questions. According to the data analysis and the structural drawing , conclusions of this study are as follows: 1.Preliminary concept of area: （1）87％ of the 6th grade students have abilities to identify with area figures and the pass rate in the straight-line figures is high. （2）first, students have the concept of telling whether the Curve figure covers an area or not and then, have the concept of telling whether the Straight and the Curve figure covers an area. 2.Conservatory concept of area: （1）85％ of the 6th grade students have the essential conservatory concept of area and 78％ students have the supplementary concept of area that represent the 6th grade students generally have the concept. （2）first, students have the essential conservatory concept of area and then, have the supplementary concept of area. 3.Measurement concept of area: （1）the pass rate of the 6th grade students in the area formula and area mapping is high. But students have to improve their ability to solve questions of measuring and comparing area through dividing, overlapping, counting and integrating. （2）Students have to master the concept of giving operation units to cover a specific figure first, and then, have the ability to solve questions about the concept of the unit side by half the volume of recovering figure. （3）Students apply the triangle area formula in the trapezoid area formula. Students have to master the triangle area formula and the parallelogram area formula and apply in solving questions of he composite area formula. （4）Students’ concept of the area mapping is established in to set a side and draw different triangles with equal area, and to draw different triangles with equal area. 4.Estimation concept of area: （1）students lack the sense of length quantity and estimate area inaccurately. （2）The concept of the area estimation of irregular figures is easy to comprehend and exists independently. （3）Students first have the concept of the area estimation of the smaller figures and then, have the concept of the area estimation of the large figures
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Liu, Chia-Ming, and 劉迦明. "A Big Data Fuzzy Grey Relational Analysis Method for Social Post Retrieval– with An Application to Facebook’s News Groups." Thesis, 2017. http://ndltd.ncl.edu.tw/handle/dcfvu4.
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碩士銘傳大學
資訊管理學系碩士班
105
Recently, the emerging big data analytics resolve the most problem of information overload. However, the current technologies of information retrieval still are unable to find user’s target posts form big data effectively. Furthermore, the application of grey system theory was rarely used to deal with big data. To resolve the problem, this study suggests and develops a big data fuzzy grey relational analysis retrieval method for social posts. After data's ETL (Extract, Transform, Load) into Spark big data platform, then user sets the criteria, goal and weight for the nonfunctional properties of the social media and sets the keywords to method for filter the candidate posts. This method use Grey Relational Analysis to proceed the parallel and distributed computing. And then, it recommends top N (top-N) social posts for users per each post’s grey relational grade. Finally, we invited 30 users to evaluate this method. The performance shows 63.91% of the correlation and 95.89% of the precision averagely. The recall is 71.62%, and the F-measure is 77.97% averagely.
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Hsieh, Kun-Lung, and 謝坤龍. "The Application of Adaptive Network-based Fuzzy Inference System and Grey Relational Analysis for Taiwanese Government Bonds Yield Prediction." Thesis, 2006. http://ndltd.ncl.edu.tw/handle/80878986695980404301.
Full textAbstract:
碩士東吳大學
經濟學系
94
The stock market and bond market are the major components of domestic financial market. The bond market has been getting more attention because of its expansion for years. Interest rate is the main variable of the operation of economic system according to economic theory. Its variation demonstrates the various development of economic and influences economic activities. The aggregate behavior of whole society can be observed through economic statistics and indices basing on the concepts of macroeconomics. Most participants of financial market also make anticipation by their changes . Therefore, this paper believes they can demonstrate the variation of government bond yield. This paper forecasts the trend of government bond yield by Multiple Regression, Grey Prediction, and Adaptive Network-based Fuzzy Inference System (ANFIS). There are lots of domestic literatures studying how to forecast the trend of government bond yield using the Neural Networks, but rare literatures adopt ANFIS. ANFIS has the advantage of both Fuzzy Logic and Artificial Neural Network. Fuzzy Logic works via the corresponding relationship of input variables and output variables. Artificial Neural Network finds the best prediction model through the training and learning of history. This paper gets the anticipation using four points rolling model and huge data which are processed by AGO adopting traditional GM(1,1) model in Grey Prediction. This paper evaluates the prediction values with RMSE and Wilcoxon Sign Test. Grey Prediction performs best in prediction according to the results.
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Liu, Ssu-Ting, and 劉思玎. "Application of PIRS and fuzzy clustering on geometrical concept structure’s analysis for first to third graders." Thesis, 2009. http://ndltd.ncl.edu.tw/handle/99021953666540352936.
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碩士國立臺中教育大學
教育測驗統計研究所
97
Geometry plays an important role in mathematical field under Grade 1-9 Curriculum. The development of students in geometry is affected by pedagogy and being familiar with the concept structure of students is helpful for teachers to design geometrical curriculum and implement their instruction. The purpose of this study is to utilize the polytomous item relational structure (PIRS) and fuzzy clustering analysis on geometrical concept diagnosis. The subjects include 340, 363 and 362 students from first grade to third grade of elementary schools. Beyond the limitation of dichotomous scoring, the polytomous geometrical concept tests are designed according to annual details of Grade 1-9 Curriculum Guidelines. The researcher classifies the whole students into groups by fuzzy clustering analysis and then analyzes the differences between the concept structures of each group displayed by PIRS. From the result of this study, several findings are concluded as following: 1.Every grade is classified into two groups by fuzzy clustering analysis and mastery of all concepts in group 1 of every grade is higher than those in group 2. 2.The concept of “being able to describe or imitate simple plane figures” is the precondition of the concept of “being able to identify, describe and classify three-dimensional shapes and simple plane figures” in both groups on first grade. 3.Linkage from “being able to recognize objects around as angles, straight lines or planes” to “being able to recognize three- dimensional shapes and simple plane figures by the relation of sides” in group 1 is the only relationship on the concept structure of second graders. 4.There are many linkages in group 1 on the concept structure of third graders.Otherwise, the only linkage in group 2 is from “being able to recognize the interior, exterior and border of plane figures” to “being able to recognize and compare the size of angles”. 5. PIRS is feasible for cognition diagnosis. The features of each group and the precondition relationship among concepts are quite varied. Finally, some suggestions and recommendations are provided for teaching and future research.
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"The Influence of Family Communication Patterns on Sexual Communication in Romantic Relationships: A Dyadic Analysis." Doctoral diss., 2016. http://hdl.handle.net/2286/R.I.38546.
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abstract: The current study employs dyadic data analysis to explore the intrapersonal and interpersonal antecedents of sexual communication in romantic relationships. Working from a family relational schema theoretical framework (family communication patterns [FCPs]; see Koerner & Fitzpatrick, 2002a), it is argued that FCPs within individuals’ family of origin structure their relational schema, which is subsequently associated with their openness and quality of sexual communication in their sexually active romantic relationships. In particular, dyadic data procedures are used to explore the interdependent influence of partners’ FCPs on reported sexual communication. It was predicted that individual (actor effects) and partner (partner effects) reports of FCPs are associated with individuals’ reports of sexual communication within romantic relationships. In addition, alternative models were proposed that predicted FCPs are associated with individuals’ self-schema (i.e., general and sexual self-concept), which is in turn associated with sexual communication. A sample of 216 heterosexual romantic dyads (N = 432) participated in a cross-sectional online questionnaire study. Results from path analyses provide partial support for hypotheses. Specifically, individuals from conversationally-oriented families tended to report higher levels of sexual communication in their romantic relationships. Also, the interaction effect between conversation and conformity orientations indicate that dyads tend to engage in more sexual communication when dyadic partners are from pluralistic families (i.e., high conversation, low conformity), and they engage in less sexual communication when partners are from laissez-faire families (i.e., low conversation, low conformity). Furthermore, FCPs were associated with the general and sexual self-concept (i.e., general self-esteem, general social anxiety, sexual self-esteem, and sexual anxiety), which in turn were associated with sexual communication. This study is important for its contribution to the family, interpersonal, and relational communication literature, as well as for its potential to expand Koerner and Fitzpatrick’s (2002a) theory of family relational schema to more domain-specific areas of communication, like sexual communication.Dissertation/Thesis
Doctoral Dissertation Communication Studies 2016
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Hsu, Hui-Fang, and 許惠芳. "Concept Structure Analysis of Number and Quantity for Second Graders based on Fuzzy Approach of Interpretive Structural Model." Thesis, 2008. http://ndltd.ncl.edu.tw/handle/51554011575272334054.
Full textAbstract:
碩士國立臺中教育大學
教育測驗統計研究所
96
The purpose of this study is to use fuzzy approach interpretive structural model (FAISM) in analyzing concept structure of mathematics indicators on number and quantity for second graders. This method integrates algorithm of fuzzy logic model of perception (FLMP) and interpretive structural model (ISM). The combined algorithm of this integrated model could analyze the individualized concept structure based on the comparisons with expert. There are totally 979 second graders in this study. The paper-pencil test on number and quantity is designed by the researcher. By using the FAISM software, we can get the diagram of individualized concept structure. The results of this study are as follows. 1.Examinees with different ability own varied ISM diagrams. 2.Examinees with the same total score but different response patterns own varied ISM diagrams. 3.Examinees of different clusters own varied ISM diagrams. 4.The similarity coefficients of ISM diagrams are both significantly different among examinees of different clusters and different ability. 5.Based on the comparisons with expert, examinees of different clusters and different ability have significantly different similarity coefficients. The results of this study can be provided as the references for cognition diagnosis, remedial teaching and courses design. At last, based on the findings and results, some suggestions and recommendations for future research are provided.
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Tang, Gwo-Hwai, and 唐國懷. "The Study of the Integration on Grey Relational Analysis and Fuzzy Assignment Problems：An Application of Military officers Assignment Model after Advanced Education." Thesis, 2008. http://ndltd.ncl.edu.tw/handle/64157358243769495549.
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碩士國防管理學院
資源管理研究所
96
According to the military target, that the post of advanced education graduation student job does not fulfill the homology then the anticipates position, the manner is denounced under the incumbency not explicit and information not integrity. The current parties job also will be subjected to the influence of sending the job number amount, can't be quickly sent the job combination, making administration efficiency not easily seen; So construct a kind of objective job model after finishing the training proper , the proper assigns the appropriate post as this research point. The first step：to arranges post after examining to preface with the grey connection analysis. The second step：to combines the personnel basic data the composing many the target is proper to go together with the comprehensive matrix, and work the condition according to the laws each kind of post, examining to not agree with the personnel who match that post, Finally, Hungary method were calculated by the combination of job. This job model finds that make three evaluation factors, can integrity present the graduation job the personnel and proper go together with the degree, to send the proper job combination to go together with the value for biggest.
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Chen, Cong-ying, and 陳淙穎. "The innovation process analysis and relational knowledgebase establishment applying in LED reading lamp by combining cloud computing concept and Petri Net theory." Thesis, 2013. http://ndltd.ncl.edu.tw/handle/93779603697388447189.
Full textAbstract:
碩士國立臺灣科技大學
機械工程系
101
The paper combines Petri net theory having process loop function with the hybrid cloud of innovative research development process of LED reading lamp. It also establishes the process design and manufacturing process related engineering knowledge and patent knowledge of LED reading lamp. After that, based on the innovative process of the paper, the paper establishes hierarchical knowledge blank field tables for relational design and manufacturing process engineering knowledgebase as well as relational design and manufacturing process patent knowledgebase, and then establishes design and manufacturing process related engineering knowledgebase and patent knowledgebase of LED reading lamp. Taking concept of remote desktop connection, the paper connects with a remote mainframe to analyze the improvement and commercial software of modified TRIZ. Furthermore, through analysis of patents, the paper judges whether new patents produced from modified TRIZ have infringed any copyrights. As mentioned above, the paper establishes an innovative development process structure that combines Petri Net with the hybrid cloud of innovative development process of LED reading lamp. In addition to design-related engineering knowledgebase and patent knowledgebase, the paper newly adds manufacturing process-related engineering knowledgebase and patent knowledgebase. Besides, the paper also uses regularization theory to analyze and improve relational knowledgebase, establishes primary keys for regularized knowledgebase, and makes it more accurate and fast during knowledgebase maintenance or knowledge renewal in future. By combining with regularization, the paper removes excessive blank field structure from knowledgebase and achieves the goal of a compact and simplified structure. In the final aspect of design, based on the design of innovative optical lampshade for LED reading lamp, the paper explains its combination of cloud computing and Petri net theory entry for computer system and search cases. For the part of manufacturing process, it is explained by the case of manufacturing process improvement of chemical mechanical polishing for hydrolytic material substrate.
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Yang, Chin-Ssing, and 楊進興. "A study on the Applications of the Analytic Hierarchy Process, the Fuzzy Theory and the Grey Relational Analysis to Establish Position Factors'' Evaluation of City Marketing ─ The case study of Taichung City." Thesis, 2004. http://ndltd.ncl.edu.tw/handle/may7na.
Full textAbstract:
碩士朝陽科技大學
企業管理系碩士班
92
As the time of the digit arrives, the boundary line between the country and country becomes more and more fuzzy. The competition of the regional city has already become one of the important subjects in the human history of social development because globalization industry’s economic activity and fast development of transnational enterprises. Taichung city is in the capital heart of the knowing area of middle part of three big city blocks of Taiwan. At present, except the problems of conformity of whole industry’s economy and unfavorable situation of social structure, she must face the stagnant problem of carrying out great construction plan in the city, insufficient human resources, such problems as the unbalanced development and confused and crowded traffic of city area. This research is from relevant documents, materials and cognition of experts and scholars of Taichung. Furthermore, it also puts the feasible city in order out, makes a reservation and orient the factor and uses the analytic hierarchy process (AHP), fuzzy theory(FT) and grey relational analysis (GRA) with the experienced information of dust and characteristic of the little data to calculate out each factor of constructing out marketing of city in Taichung. This research attempts to put forward some suggestions and views for development tactics and action scheme of city marketing in the future of Taichung. The result that the first 5 weights theory calculates out from three analysis through the analysis and comparative result from this research shows no great difference, but with consistency analogous to the degree. The goal of Taichung city on sale should focus on regional marketing of the central area in Taiwan (including Miolih, Taichung, Nantou, Changhua and Yunling, etc.). The marketing market should focus on the service of recreation consumption, and propose regarding “consume-city” as the localization of marketing of city in Taichung, so that development tactics of marketing could promote those cities in Taichung appropriately. In additional, through comprehensive assessment result, the top five factors that influence the marketing of Taichung is as the followings: Transportation services system, public security environment, communal facilities, city informationization and consumption environment, etc. Those could be reference for the relevant persons who take charge in the future development tactics in the marketing of Taichung city.
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Renda, Alessandro. "Algorithms and techniques for data stream mining." Doctoral thesis, 2021. http://hdl.handle.net/2158/1235915.
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The abstraction of data streams encompasses a vast range of diverse applications that continuously generate data and therefore require dedicated algorithms and approaches for exploitation and mining. In this framework both unsupervised and supervised approaches are generally employed, depending on the task and on the availability of annotated data. This thesis proposes novel algorithms and techniques specifically tailored for the streaming setting and for knowledge discovery from Social Networks.
In the first part of this work we propose a novel clustering algorithm for data streams. Our investigation stems from the discussion of general challenges posed by cluster analysis and of those purely related to the streaming setting. First, we propose SF-DBSCAN (streaming fuzzy DBSCAN) a preliminary solution conceived as an extension of the popular DBSCAN algorithm. SF-DBSCAN handles the arrival of new objects and continuously updates the clustering result by taking advantage of concepts from fuzzy set theory. However, it gives equal importance to every collected object and therefore is not suitable to manage unbounded data streams and to adapt to evolving settings. Then, we introduce TSF-DBSCAN, a novel "temporal" adaptation of streaming fuzzy DBSCAN: it overcomes the limits of the previous proposal and proves to be effective in handling evolving and potentially unbounded data streams, discovering clusters with fuzzy overlapping borders.
In the second part of the thesis we explore a supervised learning application: the goal of our analysis is to discover the public opinion towards the vaccination topic in Italy, by exploiting the popular Twitter platform as data source. First, we discuss the design and development of a system for stance detection from text. The deployment of the classification model for the online monitoring of the public opinion, however, cannot ignore that tweets can be seen as a particular form of a temporal data stream. Then, we discuss the importance of leveraging user-related information, which enables the design of a set of techniques aimed at deepening and enhancing the analysis. Finally, we compare different learning schemes for addressing concept-drift, i.e. a change in the underlying data distribution, in a dynamic environment affected by the occurrence of real world context-related events. In this case study and throughout the thesis, the proposal of algorithms and techniques is supported by in-depth experimental analysis.