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1
Keskin, Sinan. "Implementation Of X-tree With 3d Spatial Index And Fuzzy Secondary Index". Master's thesis, METU, 2010. http://etd.lib.metu.edu.tr/upload/12612807/index.pdf.
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Multidimensional datasets are getting more extensively used in Geographic
Information Systems (GIS) applications in recent years. Due to large volume of these
datasets efficient querying becomes a significant problem. For this purpose, before
creating index structure with these enormous datasets, choosing an efficient index
structure is an urgent necessity.
The aim of this thesis is to develop an efficient, flexible and extendible index
structure which comprises 3D spatial data in primary index and fuzzy attributes in
secondary index. These primary and secondary indexes are handled in a coupled
structure. Firstly, a 3D spatial primary index is built by using X-tree structure, and
then a fuzzy secondary index is overlaid over the X-tree structure. The coupled
structure is shown more efficient on a certain class of queries than uncoupled index
structures comprising 3D spatial data in primary index and fuzzy attributes in
secondary index separately. In uncoupled index structure, we provided 3D spatial
primary index by using X-tree index structure and fuzzy secondary index by using
BPlusTree index structure.
2
Biswas, Ajoy. "Dynamic gait stability index using a fuzzy logic model". Thesis, University of Ottawa (Canada), 2006. http://hdl.handle.net/10393/27334.
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The field of physical rehabilitation needs a quantitative technique for measuring dynamic gait stability (walking stability) to make decisions regarding treatment, assistive devices, potential for falls, and to track progress during rehabilitation. This measure should be easily applied in a clinical setting, valid across physical disabilities, and must provide a quantitative index that can be used for comparisons over a range of tasks and environments. This research project developed and evaluated a gait stability index using a portable pressure measurement system.
This study examined current stability analysis methods and evaluated dynamic gait stability assessment parameters. Six gait parameters were identified and extracted from a commercial foot pressure measurement system (F-Scan). A fuzzy logic controller combined the six parameters and generated an index value. Fifteen healthy subjects were evaluated at four stability levels. All parameter combinations (57 indices in total) were assessed to isolate the most effective index.
3
Musongole, Chibelushi Maxwell C. "Fuzzy modelling of the Johannesburg Security Exchange overall index". Doctoral thesis, University of Cape Town, 2002. http://hdl.handle.net/11427/7711.
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Bibliography: leaves 181-206.This thesis focuses on the empirical analysis of the fuzzy feature of the Johannesburg Stock Exchange Overall Index using fuzzy logic techniques. The data for the periods 1985 - 2001 is used in the analysis. Description of the fuzzy feature is crucial to the proper understanding of the movement of the JSE Overall Index and the South African economy. The fuzzy feature of the Johannesburg Security Exchange Overall Index if understood would impact on the financial and economical decisions. A preliminary Fractal analysis is carried out before the fuzzy analysis to investigate the nature of the Johannesburg Security Exchange Overall Index. The Johannesburg Security Exchange Overall Index experiences the Hurst phenomena of long memory for periods of 100 days (approximately three months). Outside the long memory periods, the Johannesburg Security Exchange Overall Index is found to exhibit antipersistent or short-range dependency characteristics. The fuzzy feature of the Johannesburg Security Exchange Overall Index is described by many aspects of fuzzy logic. The analysis of the fuzzy feature is carried out according to time periods of approximately 4 years each of the Johannesburg Security Exchange Overall Index. The index in each time period is partitioned in three fuzzy states: "low", "middle" and "high". The fuzzy states are important in assessing the fuzzy nature of the Johannesburg Security Exchange Overall Index. The partitioning reveals that the fuzzy states of the Johannesburg Security Exchange Overall Index do not possess sharp boundaries. The sizes of the fuzzy states are found to change with time. This reflects changes in the forces behind the dynamics of the index.
4
Zarei, Anahita. "A novel assessment index and intelligent predictive models for orthodontics /". Thesis, Connect to this title online; UW restricted, 2007. http://hdl.handle.net/1773/6093.
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5
Havlíček, Petr. "Spornost fuzzy logických teorií v odvozovacích systémech". Master's thesis, Vysoká škola ekonomická v Praze, 2009. http://www.nusl.cz/ntk/nusl-15839.
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This thesis focus on consistency of a specific class of fuzzy logic theories that represent certain inference system. This class of theories is defined as theories containing especially so called special axioms representing rules of modeled inference system and evaluated set of formulas representing case data. Functional approach is used to develop three popular fuzzy calculi: the Gödel logic, Łukasiewicz logic and product logic. As a language it is used the language of first order propositional fuzzy logic with valuation. To check consistency we use the concept of inconsistency degree and in Łukasiewicz logic also the principle of polar index. The concept of consistency degree is also described, but not used. Simple algorithm is developed to check consistency of theory upon the basis of inconsistency degree principle. A method of use of polar index is also described and illustrated. For each fuzzy theory a term of corresponding classical theory is defined. Then consistency of fuzzy theories and their corresponding classical theories are compared. The results of comparison are presented on the example of the ad-hoc created diagnostic inference system MEDSYS II. In the end the relation between consistency of fuzzy theory of inference system and it's corresponding theory is introduced for all three used calculi and both contradiction concepts.
6
Weil, Audrey M. "Predictors of Reasoning Ability: Working Memory Capacity and Fuzzy Processing Preference Index". Miami University / OhioLINK, 2014. http://rave.ohiolink.edu/etdc/view?acc_num=miami1397745903.
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Velayutham, Kandasamy Vivek Prasad. "Development of a Performance Index for Stormwater Pipe Infrastructure using Fuzzy Inference Method". Thesis, Virginia Tech, 2017. http://hdl.handle.net/10919/78292.
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Stormwater pipe infrastructure collects and conveys surface runoff resulting from rainfall or snowmelt to nearby streams. Traditionally, stormwater pipe systems were integrated with wastewater infrastructure through a combined sewer system. Many of these systems are being separated due to the impact of environmental laws and regulations; and the same factors have led to the creation of stormwater utilities. However, in the current ASCE Infrastructure Report Card, stormwater infrastructure is considered a sub-category of wastewater infrastructure. Stormwater infrastructure has always lacked attention compared to water and wastewater infrastructure. However, this notion has begun to shift, as aging stormwater pipes coupled with changes in climatic patterns and urban landscapes makes stormwater infrastructure more complex to manage. These changes and lack of needed maintenance has resulted in increased rates of deterioration and capacity. Stormwater utility managers have limited resources and funds to manage their pipe system. To effectively make decisions on allocating limited resources and funds, a utility should be able to understand and assess the performance of its pipe system. There is no standard rating system or comprehensive list of performance parameters for stormwater pipe infrastructure. Previous research has identified performance parameters affecting stormwater pipes and developed a performance index using a weighted factor method. However, the weighted performance index model does not capture interdependencies between performance parameters. This research developed a comprehensive list of parameters affecting stormwater pipe performance. This research also developed a performance index using fuzzy inference method to capture interdependencies among parameters. The performance index was evaluated and validated with the pipe ratings provided by one stormwater utility to document its effectiveness in real world conditions.Master of Science
8
Duprey, Benjamin Lawrence Blake. "A New Fuzzy Based Stability Index Using Predictive Vehicle Modeling and GPS Data". Thesis, Virginia Tech, 2009. http://hdl.handle.net/10919/32762.
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The use of global positioning systems, or GPS, as a means of logistical organization for fleet vehicles has become more widespread in recent years. The system has the ability to track vehicle location, report on diagnostic trouble codes, and keep tabs on maintenance schedules. This helps to improve the safety and productivity of the vehicles and their operators. Additionally, the increasing use of yaw and roll stability control in commercial trucks has contributed to an increased level of safety for truck drivers. However, these systems require the vehicle to begin a yaw or roll event before they assist in maintaining control. This thesis presents a new method for utilizing the GPS signal in conjunction with a new fuzzy logic-based stability index, the Total Safety Margin (TSM), to create a superior active safety system.
This thesis consists of four main components:
- An overview of GPS technology is presented with coverage of several automotive-based applications. The proposed implementation of GPS in the new Hardware-in-the-Loop (HIL) driving simulator under development at the Virginia Tech Center for Vehicle Systems and Safety (CVeSS) is presented.
- The three degree-of-freedom (3DOF), linear, single track equation set used in the Matlab simulations is derived from first principles.
- Matlab and TruckSim 7® simulations are performed for five vehicle masses and three forward velocities in a ramp-steer maneuver. Using fuzzy logic to develop the control rules for the Total Safety Margin (TSM), TSM matrices are built for both the Matlab and TruckSim 7® results based on these testing conditions. By comparing these TSM matrices it is shown that the two simulation methods yield similar results.
- A discussion of the development and implementation of the aforementioned HIL driving simulator is presented, specifically the steering subsystem. Using Matlab/Simulink, dSPACE ControlDesk, and CarSim RT® software it is shown that the steering module is capable of steering the CarSim RT® simulation vehicle accurately within the physical range of the steering sensor used.
Master of Science
9
Hřebíčková, Jana. "Využití fuzzy logiky pro hodnocení investičních rizik". Master's thesis, Vysoké učení technické v Brně. Ústav soudního inženýrství, 2017. http://www.nusl.cz/ntk/nusl-316944.
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This master thesis is dealing with development and application of a model that employs fuzzy logic. The model is used to support a decision of a selected Czech company that plans to invest abroad and establish a subsidiary. Selected indicators determine an investment risk in all countries considered for the investment. The model was implemented in parallel in two systems: MS Excel and MATLAB®.
10
Yeung, Fai Yip. "Developing a Partnering Performance Index (PPI) for construction projects : a fuzzy set theory approach". online access from Digital Dissertation Consortium, 2007. http://libweb.cityu.edu.hk/cgi-bin/er/db/ddcdiss.pl?3299884.
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Li, Ming. "Structural Health Monitoring Using Index Based Reasoning For Unmanned Aerial Vehicles". FIU Digital Commons, 2010. http://digitalcommons.fiu.edu/etd/241.
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Unmanned Aerial Vehicles (UAVs) may develop cracks, erosion, delamination or other damages due to aging, fatigue or extreme loads. Identifying these damages is critical for the safe and reliable operation of the systems. Structural Health Monitoring (SHM) is capable of determining the conditions of systems automatically and continually through processing and interpreting the data collected from a network of sensors embedded into the systems. With the desired awareness of the systems’ health conditions, SHM can greatly reduce operational cost and speed up maintenance processes. The purpose of this study is to develop an effective, low-cost, flexible and fault tolerant structural health monitoring system. The proposed Index Based Reasoning (IBR) system started as a simple look-up-table based diagnostic system. Later, Fast Fourier Transformation analysis and neural network diagnosis with self-learning capabilities were added. The current version is capable of classifying different health conditions with the learned characteristic patterns, after training with the sensory data acquired from the operating system under different status. The proposed IBR systems are hierarchy and distributed networks deployed into systems to monitor their health conditions. Each IBR node processes the sensory data to extract the features of the signal. Classifying tools are then used to evaluate the local conditions with health index (HI) values. The HI values will be carried to other IBR nodes in the next level of the structured network. The overall health condition of the system can be obtained by evaluating all the local health conditions. The performance of IBR systems has been evaluated by both simulation and experimental studies. The IBR system has been proven successful on simulated cases of a turbojet engine, a high displacement actuator, and a quad rotor helicopter. For its application on experimental data of a four rotor helicopter, IBR also performed acceptably accurate. The proposed IBR system is a perfect fit for the low-cost UAVs to be the onboard structural health management system. It can also be a backup system for aircraft and advanced Space Utility Vehicles.
12
Abadía, Adolfo A., i Juan Pablo Milanese. "Analysis of electoral behavior in the city of Cali using fuzzy sets. Elections for municipal mayor 2003-2011". Politai, 2015. http://repositorio.pucp.edu.pe/index/handle/123456789/92622.
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This paper aims to demystify, empirically, a statement widely shared in the political imaginary of the citizens of Santiago de Cali: candidates, who predominate in the popular sectors of the population, are the ones who win the elections for mayor («Aguablanca elects the mayor»). From an analysis with Qualitative Comparative Analysis (QCA) in their mode of fuzzy sets, it is shown that there are more complex scenarios of the electoral behavior in the elections for the municipal mayor in 2003, 2007 and 2011. Starting from this premise, from a«sociological perspective» it is proposed a classification of the strata of the city according to the pooled weighted average and candidate as elite/non elite, to analyze the electoral trends in terms of political preferences of each stratum. It also seeks to identify causal combinations that consents the election of a mayor, taking into account variables such as the profil elite/non elite of the candidates, levels of fragmentation in both segments of candidatures and finally, the dominance that each achieved in the different communes of the city.El presente trabajo se propone desmitificar, empíricamente, un enunciado ampliamente compartido en el imaginario político de los ciudadanos de Santiago de Cali: los candidatos predominantes en los sectores populares son quienes ganarán las elecciones a la alcaldía («Aguablanca elige al alcalde»). A partir de un análisis realizado con Qualitative Comparative Analysis (QCA), en su modalidad de conjuntos difusos, se muestra que existen escenarios sensiblemente más complejos del comportamiento electoral en los comicios para la alcaldía municipal en 2003, 2007 y 2011. Partiendo de esta premisa, desde una «perspectiva sociológica» del análisis electoral, se propone una clasificación de los estratos de la ciudad acorde a la media ponderada agrupada y de los candidatos como élite/no élite, para analizar las tendencias electorales en términos de expresión de preferencias políticas por parte de cada estrato. Asimismo, se busca identificar cuáles son las combinaciones causales que consienten la elección de un alcalde, teniendo en cuenta variables como: el perfil élite/no élite de los candidatos, los niveles de fragmentación existentes en ambos segmentos de candidaturas y, finalmente, el predominio que cada uno de ellos logran en las diferentes comunas de la ciudad.
13
Eleazar, Cristian Mejía Sánchez. "Control por aprendizaje neuro-fuzzy de un sistema servo-hidráulico de alta frecuencia". Universidad Nacional de Ingeniería. Programa Cybertesis PERÚ, 2011. http://cybertesis.uni.edu.pe/uni/2011/mejia_se/html/index-frames.html.
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14
Saraiya, Devang. "The Impact of Environmental Variables in Efficiency Analysis: A fuzzy clustering-DEA Approach". Thesis, Virginia Tech, 2005. http://hdl.handle.net/10919/34637.
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Data Envelopment Analysis (Charnes et al, 1978) is a technique used to evaluate the relative efficiency of any process or an organization. The efficiency evaluation is relative, which means it is compared with other processes or organizations. In real life situations different processes or units seldom operate in similar environments. Within a relative efficiency context, if units operating in different environments are compared, the units that operate in less desirable environments are at a disadvantage. In order to ensure that the comparison is fair within the DEA framework, a two-stage framework is presented in this thesis. Fuzzy clustering is used in the first stage to suitably group the units with similar environments. In a subsequent stage, a relative efficiency analysis is performed on these groups. By approaching the problem in this manner the influence of environmental variables on the efficiency analysis is removed. The concept of environmental dependency index is introduced in this thesis. The EDI reflects the extent to which the efficiency behavior of units is due to their environment of operation. The EDI also assists the decision maker to choose appropriate peers to guide the changes that the inefficient units need to make. A more rigorous series of steps to obtain the clustering solution is also presented in a separate chapter (chapter 5).Master of Science
15
Lu, Qing. "SISO and MIMO self-organizing fuzzy logic control using a dynamic performance index table : design analysis and implementation". Thesis, University of Sheffield, 2006. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.434546.
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Karanfil, Salih. "Obtaining the membership function by using the neural network in Istanbul stock exchange to find the relation between the low and closing prices". Pontificia Universidad Católica del Perú, 2014. http://repositorio.pucp.edu.pe/index/handle/123456789/96007.
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St, Clair Alison Marie. "Development of a Novel Performance Index and a Performance Prediction Model for Metallic Drinking Water Pipelines". Diss., Virginia Tech, 2013. http://hdl.handle.net/10919/19342.
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Previous authors have developed many different types of water pipe condition and failure models using the various methodologies available. Contrary, current utilities are struggling to maintain their current water infrastructure system, due to the lack of effective prediction tools at hand. The gap between the methodologies available in academic research and the tools available to current water utilities needs to be addressed. This paper presents a fuzzy inference prediction model used to forecast the performance rating of individual drinking water pipeline sections (node to node) in which utilities can easily apply to their drinking water infrastructure system.Prior to the development of a prediction model, a through literature and current practice review is completed detailing and summarizing all the available mathematical models. Following, an infrastructure overview is presented detailing the various pipe materials, lifecycle and failure modes and mechanisms. A data structure is also detailed which lists all parameters that affect the condition and/or performance of a pipeline. All of these tools are successfully used to develop a fuzzy inference performance model.
The fuzzy inference performance model is considered novel in that it considers close to 30 pipe parameters. Moreover, the performance model is applied using the Western Virginia Water Authority (WVWA) and the Washington Suburban Sanitary Commission (WSSC) databases to evaluate and verify the predicting results. Lab testing of several pipe samples is also used to evaluate the model. The testing consists of a ring bearing test which is used to calculate the rupture modulus of the pipe. Comparing the original vs. the current rupture modulus can determine the remaining strength of the pipe. The remaining strength can then be used to assess the performance results predicted by the fuzzy inference model.
Further a framework is set forth which utilizes the model\'s predicted performance ratings to develop deterioration curves which can be used as a tool to forecast and plan future inspection, repair, rehabilitation and replacement of water pipelines. The deterioration model is made up of a Markov chain approach coupled with a non-optimization technique.
Ph. D.
18
Benini, Luiz Carlos [UNESP]. "Estimação da densidade de solos utilizando sistemas de inferência fuzzy". Universidade Estadual Paulista (UNESP), 2007. http://hdl.handle.net/11449/101860.
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benini_lc_dr_botfca.pdf: 1063271 bytes, checksum: ac62bd61becd308d39b1c058ea679181 (MD5)Este trabalho tem por objetivo principal apresentar o desenvolvimento de um sistema inteligente, utilizando a Teoria Fuzzy, para estimar valores aproximados da densidade do solo a partir de medidas diretas (campo) sem a necessidade de ensaios laboratoriais e, consequentemente, identificar a compactação do solo por meio destes valores estimados. A densidade do solo é um dos principais parâmetros utilizado para a identificação do grau de compactação do solo, e está relacionada com outros parâmetros tais como a resistência à penetração do solo, o teor de água e a textura do solo. Para o desenvolvimento do trabalho foram considerados três parâmetros do solo: a resistência à penetração representado pelo índice de cone (em kPa), o teor de água dado pela umidade do solo (em porcentagem, %), e a textura dada pela quantidade de argila presente no solo (em porcentagem, %). Foram, ainda, considerados solos preparados (passagem de arado, de grade, de escarificador, e outros) e solos não preparados (nenhum tipo de preparado ou em solo de plantio direto). Segundo a porcentagem de argila no solo, estes foram divididos em solo tipo I (teor de argila menor que 30%), solo tipo II (teor de argila entre 30% e 50%), solo tipo III (teor de argila maior que 50%) para o solo não preparado, e solo tipo I (teor de argila menor que 30%) e solo tipo III (teor de argila maior que 50%) para o solo preparado. O modelo matemático proposto para determinar as estimativas da densidade do solo foi desenvolvido com base em dados experimentais representados pelas três características do solo: índice de cone, umidade e argila. Utilizando os dados experimentais os modelos foram identificados por meio de um algoritmo neuro-fuzzy, em função da resistência à penetração, teor de água e textura do solo, onde se pode analisar a densidade do solo para os distintos valores das variáveis de entradas...
The present work aims to develop a intelligent system using fuzzy theory in order to estimate approximate values for the soil density taking in account direct measurements (in loco) disregarding laboratorial essays and, consequently, to identify the compactation of the soil through those estimated values. The soil density is one of the main parameters used to identify the soil compactation level, and it is also related to other parameters such as resistance to the soil penetration, water content and soil texture. Three soil parameters were considered for the development of this work: resistance to the soil penetration represented by the cone index (in kPa), the water content given by the soil humidity (percentage, %), and the texture given by the quantity of clay present in the soil (percentage, %). Also, prepared soils were considered (plough step, grid, disk harrow, and others) as well as non prepared soils (no kind of soil preparation or direct planted soil). According to the percentage of clay in the soil, they were classified as soil type I (clay content less than 30%), soil type II (clay content between 30% and 50%), soil type III (clay content higher than 50%) for the case of non prepared soil. For the case of prepared soil it was considered only soils type I (clay content less than 30%) and type III (clay content higher than 50%). The mathematical model considered to estimate the soil density was developed on the basis of given experimental data having the three soil characteristics: Cone index, humidity and clay content. Using the experimental data the models were identified by means of a neuro-fuzzy algorithm in function of the resistance to the penetration, water content and soil texture, through which one can analyze the soil density for different values of the model entrance variables. The experimental data and the estimated ones by the model...(Complete abstract click electronic access below)
19
Ozdemir, Mustafa. "A Probabilistic Schedule Delay Analysis In Construction Projects By Using Fuzzy Logic Incorporated With Relative Importance Index (rii) Method". Master's thesis, METU, 2010. http://etd.lib.metu.edu.tr/upload/12612169/index.pdf.
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The aim of this thesis is to propose a decision support tool for contractors before the bidding stage to quantify the probability of schedule delay in construction projects by using fuzzy logic incorporated with relative importance index (RII) method. Eighty three (83) different schedule delay factors were identified through detailed literature review and interview with experts from a leading Turkish construction company, then categorized into nine (9) groups and visualized by utilizing Ishikawa (Fish Bone) Diagrams. The relative importances of schedule delay factors were quantified by relative importance index (RII) method and the ranking of the factors and groups were demonstrated according to their importance level on schedule delay. A schedule delay assessment model was proposed by using Fuzzy Theory in order to determine a realistic time contingency by taking into account of delay factors characterized in construction projects. The assessment model was developed by using Fuzzy Logic Toolbox of the MATLAB Program Software. Proposed methodology was tested in a real case study and probability of schedule delay was evaluated by the assessment model after the required inputs were inserted to software. According to the case study results, the most contributing factors and groups (that need attention) to the probability of schedule delays were discussed. The assessment model results were found to be conceivably acceptable and adequate for the purpose of this thesis.
20
Benini, Luiz Carlos 1952. "Estimação da densidade de solos utilizando sistemas de inferência fuzzy /". Botucatu : [s.n], 2007. http://hdl.handle.net/11449/101860.
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Resumo: Este trabalho tem por objetivo principal apresentar o desenvolvimento de um sistema inteligente, utilizando a Teoria Fuzzy, para estimar valores aproximados da densidade do solo a partir de medidas diretas (campo) sem a necessidade de ensaios laboratoriais e, consequentemente, identificar a compactação do solo por meio destes valores estimados. A densidade do solo é um dos principais parâmetros utilizado para a identificação do grau de compactação do solo, e está relacionada com outros parâmetros tais como a resistência à penetração do solo, o teor de água e a textura do solo. Para o desenvolvimento do trabalho foram considerados três parâmetros do solo: a resistência à penetração representado pelo índice de cone (em kPa), o teor de água dado pela umidade do solo (em porcentagem, %), e a textura dada pela quantidade de argila presente no solo (em porcentagem, %). Foram, ainda, considerados solos preparados (passagem de arado, de grade, de escarificador, e outros) e solos não preparados (nenhum tipo de preparado ou em solo de plantio direto). Segundo a porcentagem de argila no solo, estes foram divididos em solo tipo I (teor de argila menor que 30%), solo tipo II (teor de argila entre 30% e 50%), solo tipo III (teor de argila maior que 50%) para o solo não preparado, e solo tipo I (teor de argila menor que 30%) e solo tipo III (teor de argila maior que 50%) para o solo preparado. O modelo matemático proposto para determinar as estimativas da densidade do solo foi desenvolvido com base em dados experimentais representados pelas três características do solo: índice de cone, umidade e argila. Utilizando os dados experimentais os modelos foram identificados por meio de um algoritmo neuro-fuzzy, em função da resistência à penetração, teor de água e textura do solo, onde se pode analisar a densidade do solo para os distintos valores das variáveis de entradas...(Resumo completo, clicar acesso eletrônico abaixo)Abstract: The present work aims to develop a intelligent system using fuzzy theory in order to estimate approximate values for the soil density taking in account direct measurements (in loco) disregarding laboratorial essays and, consequently, to identify the compactation of the soil through those estimated values. The soil density is one of the main parameters used to identify the soil compactation level, and it is also related to other parameters such as resistance to the soil penetration, water content and soil texture. Three soil parameters were considered for the development of this work: resistance to the soil penetration represented by the cone index (in kPa), the water content given by the soil humidity (percentage, %), and the texture given by the quantity of clay present in the soil (percentage, %). Also, prepared soils were considered (plough step, grid, disk harrow, and others) as well as non prepared soils (no kind of soil preparation or direct planted soil). According to the percentage of clay in the soil, they were classified as soil type I (clay content less than 30%), soil type II (clay content between 30% and 50%), soil type III (clay content higher than 50%) for the case of non prepared soil. For the case of prepared soil it was considered only soils type I (clay content less than 30%) and type III (clay content higher than 50%). The mathematical model considered to estimate the soil density was developed on the basis of given experimental data having the three soil characteristics: Cone index, humidity and clay content. Using the experimental data the models were identified by means of a neuro-fuzzy algorithm in function of the resistance to the penetration, water content and soil texture, through which one can analyze the soil density for different values of the model entrance variables. The experimental data and the estimated ones by the model...(Complete abstract click electronic access below)
Orientador: José Ângelo Cagnon
Coorientador: Ivan Nunes da Silva
Banca: Paulo José Amaral Serni
Banca: José Alfredo Covolan Ulson
Banca: Diogenes Pereira Gonzaga
Banca: Messias Meneguette Junior
Doutor
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Santos, Francisco Carlos Barbosa dos. "Desenvolvimento e análise de um índice de sustentabilidade energética utilizando lógica fuzzy". Universidade de São Paulo, 2010. http://www.teses.usp.br/teses/disponiveis/85/85133/tde-04082011-103327/.
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A questão do Desenvolvimento Sustentável é um dos temas mais falados na atualidade, e a busca do seu entendimento um grande desafio aos pesquisadores. Mas buscar seu entendimento e as relações das dimensões que o compõe (dimensão econômica, social, ambiental e institucional) não é o único desafio. Mensurar o caminho do desenvolvimento de uma sociedade é um desafio igualmente grande, principalmente devido as intrincadas relações entre meio ambiente, sociedade e economia. Este trabalho apresenta uma nova abordagem na construção de um índice sintético de desenvolvimento sustentável do ponto de vista da sustentabilidade energética. Esta metodologia se baseou em arquétipos matemáticos estruturados na Lógica Fuzzy, permitindo assim incorporar novas bases de conhecimento, mesmo que com definições vagas. O resultado final é a criação de um Índice de Sustentabilidade Energética que pode ser acompanhado no tempo, e que permite comparações entre países, já que na sua construção utiliza-se a base de dados do Guia de Indicadores Energéticos de Desenvolvimento Sustentável da Agência Internacional de Energia Atômica, que apresenta uma metodologia mundialmente aceita de indicadores energéticos. Este índice foi concebido para se parecido com outros indicadores como Índice de Desenvolvimento Humano (IDH) elaborado pela Organização das Nações Unidas, o que permite um fácil entendimento, por ser um número entre zero e um.Sustainable Development is one the most frequently addressed issues nowadays and the search for its comprehension is a major challenge for researchers. Nevertheless, to reach its understanding and the relations comprised (economic, social, environmental and institutional dimensions) is not the only challenge. To measure the route for a society development is an equally important matter, mainly due to intrinsic relations among environment, society and economy. This work presents a new approach in the construction of a synthetic index for sustainable development, under the point of view of energy sustainability. This methodology was based on mathematical archetypes structured in Fuzzy Logics, thus allowing the incorporation of new knowledge bases, even with vague definitions. The final result is the creation of an Energy Sustainability Index that may be accompanied along the time, allowing comparisons among countries, since it uses a database from the Guia de Indicadores Energéticos de Desenvolvimento Sustentável (Guide of Energy Indicators for Sustainable Development) from the IAEA. This guide presents an energy indicator methodology worldwide accepted and it was conceived to be similar to other indicators, such as the Índice de Desenvolvimento Humano (IDH) (Human Development Index), developed by The United Nations Organization and which is of easy comprehension, since it is represented by a number between zero and one.
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Hong, Sui. "Experiments with K-Means, Fuzzy c-Means and Approaches to Choose K and C". Honors in the Major Thesis, University of Central Florida, 2006. http://digital.library.ucf.edu/cdm/ref/collection/ETH/id/1224.
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This item is only available in print in the UCF Libraries. If this is your Honors Thesis, you can help us make it available online for use by researchers around the world by following the instructions on the distribution consent form at http://library.ucfBachelors
Engineering and Computer Science
Computer Engineering
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Barcellos, de Paula Luciano, i Lafuente Ana María Gil. "Algoritmo aplicado en el diálogo con los grupos de interés: un estudio de caso en una empresa del sector turismo". Pontificia Universidad Católica del Perú, 2012. http://repositorio.pucp.edu.pe/index/handle/123456789/114839.
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According to numerous scientific studies one of the most important points in the area of sustainability in business is related to dialogue with stakeholders. Based on Stakeholder Theory we try to analyze corporate sustainability and the process of preparing a report that a company in the tourism sector in accordance with the guidelines of the guide G3 - Global Reporting Initiative. With the completion of an empirical study seeks to understand the expectations of stakeholders regarding the implementation of the contents of the sustainability report. To achieve the proposed aim we use «The Expertons Method» algorithm that allows the aggregation of opinions of various experts on the subject and represents an important extension of fuzzy subsets for aggregation processes. At the end of our study, we present the results of using this algorithm, the contributions and future research.De acuerdo con numerosos estudios científicos uno de los puntos más importantes en el ámbito de la sostenibilidad en las empresas radica en el diálogo con los grupos de interés. Tomando como base la teoría de los grupos de interés, trataremos de analizar la sostenibilidad empresarial y el proceso de elaboración de un informe que una empresa del sector de turismo prepara de acuerdo con las directrices de la guía G3, Global Reporting Initiative (GRI). Con la realización de un estudio empírico se pretende conocer las expectativas de los grupos de interés con respecto al cumplimiento del contenido de la memoria de sostenibilidad. Para alcanzar el objetivo propuesto utilizaremos el «método de los expertones», algoritmo que permite la agregación de opiniones de varios expertos sobre el tema y que representa una importante extensión de los subconjuntos borrosos para procesos de agregación. Al final de nuestro estudio, presentaremos los resultados de la utilización de este algoritmo, las aportaciones y futuras líneas de investigación.
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Pessoa, Marco Antonio Ribeiro. "IQAFAL - Índice Fuzzy de Qualidade de Água para Ambiente Lótico". Universidade do Estado do Rio de Janeiro, 2010. http://www.bdtd.uerj.br/tde_busca/arquivo.php?codArquivo=2926.
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A divulgação de informação sobre qualidade das águas para um público não especialista é fundamental para subsidiar ações políticas e institucionais de gestão dos ambientes aquáticos. Para tanto, índices de qualidade de água têm sido propostos por serem capazes de sintetizar em um único valor ou categoria a informação normalmente descrita a partir de um conjunto extenso de variáveis químicas, físicas e biológicas de qualidade de água. A maioria das metodologias propostas para o desenvolvimento de índices de qualidade de água é baseada no conhecimento de especialistas quanto à escolha das variáveis a serem utilizadas, a ponderação da importância relativa de cada variável e métodos utilizados para agregar os dados das variáveis em um único valor. Este trabalho propõe um novo índice de qualidade de água, baseado em lógica nebulosa e direcionado para o ambiente lótico. Esse índice, o IQAFAL, foi desenvolvido com a colaboração de especialistas com ampla e comprovada experiência na área de qualidade de água. A essência do desenvolvimento de um índice, usando-se lógica nebulosa, está na capacidade dessa metodologia representar, de forma mais eficiente e clara, os limites dos intervalos de variação dos parâmetros de qualidade de água para um conjunto de categorias subjetivas, quando esses limites não são bem definidos ou são imprecisos. O índice proposto neste trabalho foi desenvolvido com base no conhecimento dos especialistas em qualidade de água do Instituto Estadual do Ambiente - INEA e aplicado aos dados de qualidade de água do Rio Paraíba do Sul, obtidos pelo INEA, nos anos de 2002 a 2009. Os resultados do IQAFAL mostraram que esse índice foi capaz de sintetizar a qualidade da água deste trecho do Rio Paraíba do Sul correspondendo satisfatoriamente às avaliações de qualidade de água descritas nos relatórios disponíveis. Verificou-se também que com essa metodologia foi possível evitar que a influência de uma variável em condições críticas fosse atenuada pela influência das outras variáveis em condições favoráveis produzindo um resultado indesejável no índice final.The dissemination of information on water quality for a non-specialist audience is essential to support programs and institutional policies for the management of aquatic environments. Therefore, water quality indices have been proposed since they are able to synthesize into a single value or category information usually described from an extensive set of chemical, physical and biological water quality variables. Most of the proposed methodologies for the development of water quality indices are based on expert knowledge regarding the choice of variables used, weighting the relative importance of each variable, and methods used to aggregate data variables in a single value. This research proposes a new index of water quality, based on fuzzy logic and aimed at the lotic environment. This index, the IQAFAL, was developed through the collaboration of experts with broad and proven experience in the area of water quality. The essence of developing an index, using fuzzy logic is the ability of that methodology to represent, more efficiently and clearly, the limits of the ranges of the variables of water quality for a set of subjective categories, where these limits are not well defined or are inaccurate. The index proposed in this paper was developed based on knowledge of experts in water quality of the Rio de Janeiro Environmental Agency - INEA and applied to data of water quality of the Paraíba do Sul river, obtained by INEA, in the years 2002 to 2009. The results of IQAFAL showed that the index was able to synthesize the water quality of this stretch of the Paraíba do Sul, corresponding satisfactorily to the assessments of water quality described in the reports available. It was also noted that with this methodology it was possible to avoid the attenuation of the influence of a variable in critical condition by the influence of other variables in good conditions producing an undesirable result in the final index.
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AraÃjo, Juliana Alencar Firmo de. "Desenvolvimento de uma Metodologia, com base na Teoria Fuzzy, para o Estudo do Risco de EutrofizaÃÃo em ReservatÃrios com Estudo de Caso no ReservatÃrio Acarape do Meio do Estado do CearÃ". Universidade Federal do CearÃ, 2011. http://www.teses.ufc.br/tde_busca/arquivo.php?codArquivo=6180.
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CoordenaÃÃo de AperfeiÃoamento de Pessoal de NÃvel SuperiorOs processos de eutrofizaÃÃo em reservatÃrios constituem-se como um dos mais importantes problemas de qualidade de Ãgua a ser estudado por engenheiros, cientistas e gestores de recursos hÃdricos. Como se sabe, em regiÃes de escassez, o armazenamento de Ãgua à de fundamental importÃncia para o desenvolvimento sustentÃvel, tanto do ponto de vista econÃmico, como do ponto de vista social. Assim, adquirir conhecimento que explique os principais fatores nos processos de eutrofizaÃÃo à um desafio. Este trabalho tem como objetivo fundamental, o desenvolvimento de uma metodologia capaz de estudar o risco de eutrofizaÃÃo de um reservatÃrio, com base na Teoria Fuzzy e nos mecanismos usados para a determinaÃÃo dos Ãndices do Estado TrÃfico Modificado (IETM). Para tal, foram usados dados do ReservatÃrio Acarape do Meio, no estado do CearÃ, notadamente, nos anos de 2001 atà 2006, sendo que no ano de 2003 nÃo houve visita ao campo por parte da Companhia de GestÃo de Recursos HÃdricos â COGERH. Para o cÃlculo do risco foram usadas funÃÃes de pertinÃncia do Ãndice de Estado TrÃfico Modificado, transformadas segundo as regras dos NÃmeros Difusos. Os resultados mostram que para os anos observados, somente em 2006 a qualidade das Ãguas daquele reservatÃrio ficou em estado crÃtico.
The processes of eutrophication in reservoirs become as an important problem in water quality to be studied by engineers, scientists and water managers. As it is known, in areas of scarcity, water storage is of fundamental importance to sustainable development, both from an economic standpoint, as the social point of view. Thus, acquiring knowledge that explains the main factors in eutrophication processes is a challenge. This work has as fundamental goal, the development of a methodology capable of studying the risk of eutrophication in a reservoir, based on Fuzzy Theory and the mechanisms used for the determination of the Modified Trophic State Index. In such way, it was used data from the Acarape do Meio Reservoir, in the State of CearÃ, especially in the years 2001 to 2006, but in 2003 there were not field visits by the Company of Water Resources Management - COGERH. To calculate the risk it was used membership functions of the Modified Trophic State Index, transformed according to the rules of Fuzzy Numbers. The results show that for the years of observation, only in 2006 the reservoir water quality was in critical condition.
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Garg, Arun. "Quantifying resilient safety culture using complex network theory". Thesis, Griffith University, 2022. http://hdl.handle.net/10072/411532.
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Safety is defined as the absence of accidents where accident is an event which lead to unacceptable loss. Previously, most systems employed conventional risk management systems to deal with risks which was based on knowledge of previous experiences, failure reporting and risk assessments by computing historic data. But today, these are traced to organizational factors, functional performance variability and unexpected outcomes or it can be pointed towards systems thinking. Resilience engineering is recognized as other alternative to traditional approaches in safety management. The idea behind resilience engineering is that an organization must continually manage risks and create an anticipating, monitoring, responding and learning culture. This is resilient safety culture. Resilient safety culture is a new concept which has been proposed in order to cover the weaknesses of traditional approaches of safety culture. It is a safety culture with resilience, learning, continuous improvements and cost effectiveness. This resilience takes into consideration the dynamic aspect of the safety culture which makes it resilient to any risks which a safety system faces. The main drawback is the dynamic aspect of the culture is not taken into consideration which is the interaction between people, technology and administration. These interactions are quite complex in nature and difficult to understand and quantify. That is why this study investigates the understanding of these interactions using complex network theory. Once these interactions are understood to some extent, the prediction and prevention of incidents can be done to some extent.
There are four different kinds of indicators in the system. Two are system performance indicators, leading and lagging and the other two are the risk indicators that as well leading and lagging. The system performance indicators are indicators which show how the system is performing either in current state which is leading and the system performance indicator which is lagging is gauged by efficiency of the system after a time such as injury rate. Risk indicators leading is found by understanding the various risks which are prevalent in the system and lagging risk indicators are the indicators which led to an accident in previous time frame. Since the system is dynamic, it needs to be understood that these indicators have a time value attached to it. If there is an accident which happened due to some lagging risk indicator, that is in previous time frame, that may have already changed by the time the accidents happened so safety-1 concept which looked at just lagging indicators to dictate the future evaluations of the organization need to be modified and thus resilient safety culture methodology is getting evolved using resilience engineering.
Using fault tree analysis, the interactions of various components in a safety system can be understood. Resilient safety culture is treated as a system and it has three sub systems. The sub system further has factors which are important relationships to understand the whole system. These relations between the factors and subsystem are used to measure the resilience of the whole system. This is an innovative quantifying way in which we can improve the resilience in safety culture of an organization.
In this study, the qualitative variables defined using the literature are correlated using qualitative as well as quantitative approaches. In the qualitative approach, Leximancer tool is used which model the variables using the literature data. Next, the resilient safety culture model is generated and then fault tree analysis is used to decipher the complex interactions which can help understand which relationships can lead to incident. This study would generate a tool which would help organizations look at the weak links and nodes in their organization to better equip and enhance resources to make the organization more resilient against any safety risks. Multiple case studies are done to validate this model and to show how the whole process is done to understand a way to reduce and mitigate risks. Resilience index is generated which helps in finding which constructs are lagging or weak in giving that index number and the index can be used to compare to companies or organizations irrespective of the number of respondents or the type of indicators which are used. It also helps in reducing the linguistic bias.
The findings of this study show that in resilient safety culture model, which components should be focussed first and how the components of resilient safety culture model are related with each other. This helps in optimization of the components or subcomponents to get the maximum resilience in an organization. It is also found that weak areas in an organization can be successfully deciphered using the fault tree analysis approach along with visualization of failure paths.
This resilience safety culture model generated along with the methodology adopted in this study can help the industry to making right decisions in enhancing the resilience of the organizations with minimum intervention. It can help the industry find the weak areas where the intervention is needed. It can also give leading indicators which can cause future incidents.Thesis (PhD Doctorate)
Doctor of Philosophy (PhD)
School of Eng & Built Env
Science, Environment, Engineering and Technology
Full Text
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Elshahat, Ayah Elsayed. "Enhancing nuclear energy sustainability using advanced nuclear reactors". Thesis, University of Manchester, 2015. https://www.research.manchester.ac.uk/portal/en/theses/enhancing-nuclear-energy-sustainability-using-advanced-nuclear-reactors(2c39b9ca-86a9-446f-8832-ae9469485a2d).html.
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The safety performance of nuclear power reactors is a very important factor in evaluating nuclear energy sustainability. Improving the safety performance of nuclear reactors can enhance nuclear energy sustainability as it will improve the environmental indicator used to evaluate the overall sustainability of nuclear energy. Great interest is given now to advanced nuclear reactors especially those using passive safety components. Investigation of the improvement in nuclear safety using advanced reactors was done by comparing the safety performance of a conventional reactor which uses active safety systems, such as Pressurized Water Reactor (PWR), with an advanced reactor which uses passive safety systems, such as AP1000, during a design basis accident, such as Loss of Coolant Accident (LOCA), using the PCTran as a simulation code. To assess the safety performance of PWR and AP1000, the “Global Safety Index” GSI model was developed by introducing three indicators: probability of accident occurrence, performance of safety system in case of an accident occurrence, and the consequences of the accident. Only the second indicator was considered in this work. A more detailed model for studying the performance of passive safety systems in AP1000 was developed. That was done using SCDAPSIM/RELAP5 code as it is capable of modelling design basis accidents (DBAs) in advanced nuclear reactors.
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Tseng, Chun-Hao. "Safety performance analyzer for constructed environments (SPACE)". Columbus, Ohio : Ohio State University, 2006. http://rave.ohiolink.edu/etdc/view?acc%5Fnum=osu1148572816.
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Brancalioni, Ana Rita. "PROPOSTA DE CLASSIFICAÇÃO DA GRAVIDADE DO DESVIO FONOLÓGICO POR MEIO DA MODELAGEM FUZZY, SEGUNDO O MODELO IMPLICACIONAL DE COMPLEXIDADE DE TRAÇOS". Universidade Federal de Santa Maria, 2010. http://repositorio.ufsm.br/handle/1/6484.
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Coordenação de Aperfeiçoamento de Pessoal de Nível SuperiorThis study aimed at proposing a quantitative classification for phonological disorder severity based on the Implicational Model of Feature Complexity IMFC (MOTA, 1996), considering Rangel s adequacies (1998). Quantification of such proposal was based on the Fuzzy modeling; to do so, a Linguistic Fuzzy Model was created, developed from a system of fuzzy rules, processed in parallel, using Mamdani s minimum inference method and the center of area defuzzification method. The Model comprehended three input variables: Path Course, Level of Complexity and Acquisition of Phonemes, described in linguistic terms to which fuzzy subsets were added (three subsets for each variable). Determination of borders followed criteria and inference based on the IMFC and on the researcher s experience. The model output variable was the Severity Phonological Disorder Index based on four fuzzy subsets: Severe, Moderate-Severe, Moderate-Mild, and Mild. The Severity Phonological Disorder Index was calculated for all 204 deviating phonological systems included in the sample using the Fuzzy Linguistic Model, run in MATLAB fuzzy toolbox (2009b). Validation of modeling was performed by evaluating severity of a representative number of phonological systems by two groups of speech and language therapists. The first, GT-I (Group of Speech and Language Therapists I), was comprised of three speech and language therapists with a doctorate in applied linguistics and experienced in disordered speech. The second, GT-II (Group of Speech and Language Therapists II), was comprised of three speech and language therapists with a master s degree in human communication disorders and experienced in disordered speech at a research laboratory. Classification of disorder severity based on the proposal was similar to that assessed by the speech and language therapists in most phonological systems under evaluation. In addition, the criteria used in the proposal were used by Group I speech and language therapists and were considered adequate by Group II. Finally, the proposal has shown to be able to quantitatively differentiate degrees as to input variables (path course, level of complexity, acquisition of phonemes), sound classes, and distinctive features. Such findings allowed the conclusion that the proposal is able to adequately classify phonological disorder severity and presents validity for the speech and language therapists; therefore, it is an important reference for clinical practice.
Este estudo teve como objetivo propor uma classificação quantitativa para a gravidade do desvio fonológico a partir do Modelo Implicacional de Complexidade dos Traços MICT (MOTA, 1996), considerando as adequações de Rangel (1998). A quantificação da proposta foi fundamentada na modelagem Fuzzy, para isso, criou-se um Modelo Linguístico Fuzzy, desenvolvido a partir de um sistema de regras fuzzy, processadas em paralelo, utilizando como método de inferência o Mínimo de Mamdani e como método de defuzzificação o centro de área. O Modelo englobou três variáveis de entrada: Percurso das Rotas, Nível de Complexidade e Aquisição dos Fonemas, descritas em termos linguísticos aos quais se associaram subconjuntos fuzzy (três subconjuntos para cada variável). A determinação das fronteiras seguiu critérios e inferências a partir do MICT e da experiência do pesquisador. A variável de saída do modelo foi o Índice de Gravidade do Desvio Fonológico a partir de quatro subconjuntos fuzzy: Grave, Moderado-Grave, Moderado-Leve e Leve. O Índice de Gravidade do Desvio Fonológico foi calculado para os 204 sistemas fonológicos desviantes que compuseram a amostra, através do Modelo Linguístico Fuzzy, executado no toolbox fuzzy do software MATLAB (2009b). A validação da proposta foi realizada através do julgamento da gravidade, de um número representativo de sistemas fonológicos, por dois grupos de fonoaudiólogas. O primeiro, GF-I (Grupo de Fonoaudiólogas I), composto por três fonoaudiólogas, doutoras em linguística aplicada e experientes em fala com desvio. O segundo, GF-II, (Grupo de Fonoaudiólogas II) composto por três fonoaudiólogas, mestres em distúrbios da comunicação humana e experientes em fala com desvio em laboratório de pesquisa. A classificação da gravidade do desvio a partir da proposta foi semelhante à julgada pelas fonoaudiólogas na maioria dos sistemas fonológicos avaliados. Além disso, os critérios utilizados na proposta foram utilizados pelas fonoaudiólogas do Grupo I e foram julgados adequados pelo Grupo II. Por fim, verificou-se que a proposta é capaz de diferenciar quantitativamente os graus quanto às variáveis de entrada (percurso das rotas, nível de complexidade, aquisição dos fonemas), às classes de sons e aos traços distintivos. Tais achados permitiram concluir que a proposta é capaz de classificar a gravidade do desvio fonológico adequadamente e apresenta validade para as fonoaudiólogas sendo, portanto, importante referência para a prática clínica.
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Shao-WeiTsai i 蔡紹緯. "Intuitionistic fuzzy hierarchical clustering and validity index". Thesis, 2014. http://ndltd.ncl.edu.tw/handle/26616418935404605620.
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碩士國立成功大學
工業與資訊管理學系
102
Clustering analysis is a traditional statistical tool that is used for data classification. While data is often described using crisp numbers, this has some limitations with regard to representing the uncertainties inherent in many situations, and thus so-called fuzzy approaches have been developed to deal with this. An intuitionistic fuzzy set (IFS) is a set of 2-tuple arguments, which are characterized by the properties of membership and non-membership. This paper develop a new clustering analysis method to carry out the data description by IFS. There are two stage in this method. In the calculating state, the similarity method proposed by Liang and Shi (2003) is used to measure the distance between two data points and then combine the most similar data. After data integration, the similarity between the integrated data and the rest of data is assessed, and if this similarity greater than the value of , which is decided by a decision-maker, then a second round of integrated is carried out. This then continues until all of the data is integrated, and then a hierarchical structure of the data cluster can be obtained. In the assessment stage, a modified version of the validity index proposed by Babak (2010) is used to measure the clustering results to find the optimal number of clusters. Comparison of the proposed method with other IFS clustering approaches shows that the method developed in this work achieves similar clustering results, but can return more distinct clusters to the decision-maker, and thus provide more useful information. In summary, this study provides a new IFS hierarchical clustering method that is more flexible than existing approaches and can produce clearer clustering results.
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chiang, san, i 江珊. "Forecasting Leading Index using Fuzzy Prediction System". Thesis, 2002. http://ndltd.ncl.edu.tw/handle/22024487754342378414.
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碩士淡江大學
資訊工程學系
90
Leading Index is made from those indexes that could be able to reflect in front of prosperity change. The prosperity will revive while Leading Index is rising continue three months. On the other hand the prosperity will come down while Leading Index is descending continue three months. Many researcher point out that Leading Index come down 1~2% and descending through 6 months means prosperity will come down. The Leading Index include 7 indexes: the change rate of manufacturing’s new order, the average working hours of one month of manufacturing, houses and buildings apply for superficial contents, the change rate of export value, the change rate of wholesale, the change rate of money supply and the change rate of stock price. In this paper, we proposed a Fuzzy Prediction System to predict the Leading Index. There are two parts in our system: one is Fuzzy Linguistic Summary the other is Fuzzy Stochastic Prediction. Users can classified data using Fuzzy Linguistic Summary, and using Fuzzy Stochastic Prediction to generate a predicted values. Not only our method can predict leading index but also can predict a company’s revenue. In this paper, we use fuzzy theory to set the parameter of Fuzzy Stochastic Prediction. To demonstrate our method work correctly, we use our method to compare with Regression Prediction and Dynamic Grey Prediction. The result shows that our method is more accurately.
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Liou, Yi-Ting, i 劉怡廷. "The establishment of Factor Water Qulaity Index and Fuzzy Water Qulaity Index". Thesis, 2004. http://ndltd.ncl.edu.tw/handle/32267506843694133778.
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博士國立臺灣大學
環境工程學研究所
92
An index system to condense efficiently monitoring data based on fuzzy logic and factor analysis is proposed. Fuzzy membership functions for the variables of quality assessment in water are constructed as uniformly decreasing functions and unimodal distributions on the interval [0, 1], with relating the various levels of variable measurements to the appropriate levels of water quality. Membership values of the variables are most categorized into three contaminated aspects referred to the factor analysis, which are “organics”, “particulates” and “salty matter” and recognized as the three common features of water quality evaluation. The membership values of variables of pH, temperature and toxic substances are categorized into a specific “independent” aspect for the different contaminated characteristic and membership distributions from the three common features. The minimum operator is used as an aggregation function for the memberships of the three defined aspects and the specific independent aspect to yield an overall single numerical value. The geometric mean is used to aggregate the membership values of variables that specify to the three defined contaminated aspects and the arithmetic mean is used to aggregate the membership values of variables associated in the same aspect. This study proposes a fresh, solid structure to produce an index system and which deals with the incompleteness of the measurements appropriately and reveals the effects of events on quality of water correctly. Besides, an index model for the water quality evaluation and trophic evaluation of reservoir waters is proposed based on the convergent theory of fuzzy c-means. Sums of the degrees of similarity derived from the extended fuzzy c-means algorithm are used to construct an alternative overall index. The stretching values of the controlling parameters in the convergent theory of fuzzy c-means are discussed with reference to final performances for the evaluation, consecutive analysis or categorized classification. As a result, the ability of the proposed model aggregates the measurements of environmental quality in categories as well as in trends analysis.
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Tsai, Yi-Jhang, i 蔡宜璋. "Index Portfolio Construction Based on Fuzzy Goal Programming". Thesis, 2011. http://ndltd.ncl.edu.tw/handle/70838623269197700937.
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碩士國立中興大學
科技管理研究所
99
Mutual fund is one of favorite tools of the investors. Individual investors need no efforts on stock-picking and market-timing because the investing risk can be lowered through the professional management. But the researches indicate that most actively managed mutual fund’ performance is difficult to beat the market, and index investing is more and more popular among the investors. Index investing instruments, such as index funds and ETFs, aim to track the market performance. In practical, an index tracking portfolio has to pay the transaction cost due to following the change of benchmark index and also has to remain certain cash position. This result in the higher tracking error, therefore we want to pursuit both tracking error minimization and excess return maximization to attain the real performance tracking. Both are conflicting objectives. Goal programming is suitable for handling multiple conflicting objectives, but the basic goal programming concept is first to set up the crisp goals. In the real financial environment, the desired/expected level of the decision maker is usually imprecise. Minimizing the tracking error and maximizing the excess return are both represented as “fuzzy goals” in this research. Results show that through certain membership function and tracking model, an index tracking portfolio whose tracking error is lower than 0050 index fund but excess return is similar to 0050 index fund can be constructed.
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Wu, Chang-Che, i 吳昌哲. "Fuzzy Time Series and Fuzzy GARCH Model for Forecasting the BDI (Baltic Dry Index)". Thesis, 2009. http://ndltd.ncl.edu.tw/handle/62329021826454849942.
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碩士萬能科技大學
經營管理研究所
97
Past study in the Fuzzy time series prediction model for the history of Fuzzy time series data have the advantage and to establish a simple relationship between the fuzzy logic way of doing group forecast accurately the value of traditional time series methods in the develop-ment of prediction models is already quite complete and mature. But only in the precise value of the historical time series prediction and there is the risk of over-fitting. This study will be combined with Fuzzy time series with the precise value of the tradi-tional advantages of time series. The fuzzy interval of time after the sequence of construction of a Fuzzy Generalized Autoregressive Conditional Heteroskedasticity (Fuzzy-GARCH) pre-diction model Fuzzy-GARCH then forecast generalization process. The sample is using the new system the Baltic Freight Index (BDI) the actual closing price during the week of data. It is from January 2006 until 1st week first in May 2009 only 1st week. It is total of 174 as the empirical research data. Fuzzy time series compared with the Fuzzy-GARCH's predictive ca-pability and index information to the BDI in order to verify the information. The results showed that the samples in the same period of the forecast weeks forecast information on the BDI. RMSE of Fuzzy-GARCH is 210, MAE of Fuzzy-GARCH is 159, MAPE of Fuzzy-GARCH is 10.03%, they are compared with the fuzzy time series, RMSE of fuzzy time series is 285, MAE of fuzzy time series is 237, MAPE of fuzzy time series is 15.17%, had better predictive power in the Baltic index data validation. Fuzzy-GARCH time series compared with the fuzzy also verify have better predictive power. Fuzzy-GARCH value compared to traditional time-series model accurately define the scope of the prediction interval in order to comply with the logic of human thinking and decision making predictive capability in comparison to the fuzzy time series is a better predictive capability.
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鄭淙仁. "Forecasting Taiwan Weighted Stock Index with Fuzzy Time Series". Thesis, 2002. http://ndltd.ncl.edu.tw/handle/81625593557966548327.
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碩士國立海洋大學
航運管理學系碩士在職專班
90
This study contributes to forecast Taiwan Weighted Stock Index with fuzzy time series. In consideration about applying some traditional time series model to forecast is so much on complicated computation even if it is well accomplished by the electronic computers. It is a hard job to do so. However, forecasting with fuzzy time series model is easier and simpler in mathematical operation and the result keeps better. Therefore, it is worthy to promote this way for forecasting. In 1996, Chen proposed a new simplified fuzzy time series model that converted all complex matrix operation into simple arithmetic operation. His result was shown better than the essential Song-Chissom model’s. He reduced very huge cost in computation and he could obtain superior accuracy without any computer aided operation. But Chen’s method still has some points that can be improved. The major point aims at that he never considers the probability of each event. This study will focus on this point and correct it for achieving some improvements. It gives each event an equal weight number then calculates with Chen’s model. The gains figure out some obvious improvements than Chen’s. The average error rate falls from 1.3% to 1.12% and the R.M.S.E. also declines from 92.41 to 78.78.
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Chen, Chia-Hui, i 陳家慧. "Development of Fuzzy Service Capability Index in Supplier Selection". Thesis, 2010. http://ndltd.ncl.edu.tw/handle/59120621252132805793.
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碩士亞洲大學
經營管理學系碩士班
98
Supplier selection is very important and complex problem for the businessman. The master have to make the correct decision before consider the different evaluation guideline. The fuzzy linguistic variable transformed to a crisp number through the fuzzy theory. And use the Service Capability Index to measure the service quality of suppliers. As the technological change and the environment, there are more and more important about the quality requirements of the tangible products or intangible services for people, and customers often judge the service quality based on interactions observing leads with services providers. Thus, the service quality can influence customer repurchase intentions, and then affect business performance. However, the service quality were an expression of sensitivity and subjective questions, when people are thinking or decision-making, often they will have vague and personal preferences. Therefore, the present project in this pipeline fuzzy linguistic values so that customers can more specifically described as a crisp value by applying fuzzy theory. In addition, this is a larger-the-better, when the service quality in customers or companies for the higher (large) as possible. So according to Cpl in the PCI, we will construct Spl, and then this project SCI brings many customers crisp values when they were feelings of the service time. Final evaluation the overall service quality levels by different service providers, and the result can provide companies improvements that influence customers repurchase intentions.
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You, Shih-Syuan, i 游士萱. "Establishing Fuzzy Regression Models Based on Modified Dissemblance Index". Thesis, 2011. http://ndltd.ncl.edu.tw/handle/54960022093017736223.
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Hsu, Fang-Yu, i 徐芳瑜. "Fuzzy-Switch TGARCH Model Applied to Stock Market of NASDAQ Index and Taiwan Weighted Index". Thesis, 2004. http://ndltd.ncl.edu.tw/handle/77580902017662778358.
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碩士嶺東技術學院
財務金融研究所
92
This paper considers transmissions of volatility in time-varying nonlinear and asymmetric models. Generally, there are many complex factors that can affect transmissions of volatility such as good news and bad news. To account for these elements, we adopt artificial intelligence methodology and propose a Fuzzy-Switch TGARCH model. Specifically, the threshold value in a conventional TGARCH model is modified using rules borrowed from fuzzy logic. Simulations for the NASDAQ index and Taiwan weighted index from January 6, 1992, to June 27, 2002, indicate that transmissions of volatility for the NASDAQ index and Taiwan weighted index are time-varying nonlinear and asymmetric. Furthermore, empirical results demonstrate improved accuracy with a Fuzzy-Switch TGARCH model over the traditional GARCH and TGARCH models.
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Sun, Yat-sen, i 卓福明. "Forecasting Taiwan’s Stock Index Using New Fuzzy Time Series Models". Thesis, 2008. http://ndltd.ncl.edu.tw/handle/95610536281232565575.
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碩士逢甲大學
國際貿易所
96
Stock market is market or the trading of company stock, and derivatives of same; both of these are securities listed on a stock exchange as well as those only traded privately. The stock market is one of the most important sources for companies to raise fund. This allows businesses to go public, or raise additional capital for expansion. The liquidity that an exchange provides affords investors the ability to quickly and easily sell securities. This is an attractive feature of investing in stocks, compared to other less liquid investments such as real estate. The objective of this study is to apply the neural networks to implement a new fuzzy time series model to forecast the Taiwan’s stock index price. The neural networks represent knowledge bases on massive parallel processing and pattern recognition based on past experience or examples. Neural networks were also considered to outperform standard statistical models in forecasting with a small-sized training set and high level of white noise. In this paper the neural networks are used to compute the degrees of memberships and then fuzzy relationships. The fuzzy relationships are then used to forecast the stock index price in Taiwan. Using Taiwan stock index price data during 1971 and 2006, this paper attempts to learn the historical data and establish a new fuzzy time series model. Then the model will be applied to estimate Taiwan’s stock index price. The forecasts will be compared with the actual data concerning the RMSE and empirical analysis will be conducted.
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Liu, Mei-fen, i 劉美芬. "Fuzzy Approach of Time Management, Job Stress Index,and Leisure Activity Index for Elementary School Principals". Thesis, 2013. http://ndltd.ncl.edu.tw/handle/56614736343169771934.
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博士國立暨南國際大學
教育政策與行政學系
101
This study attempts to explore time management, job stress index, and leisure activity index for elementary school principals. Under the trends in globalization and commodity marketing, accountability has received more attention for school principals, and thus more stress has come from many aspects. Evaluation of time management and analysis of individual stress index to form good habits of leisure activity may help relieve job stress and enhance school effectiveness. Fuzzy questionnaire survey, fuzzy modes, fuzzy mean, fuzzy weight, intervals, and Wilcoxon rank-sum test were used to compare with each other in order to analyze interviewees’ current status of time management, stress, and leisure activity. Finally, the indicators of measuring time management, job stress, and leisure activity were constructed in the study for promoting leadership. Meanwhile, based on the results of study, some suggestions were made for school principals to improve their time management, job stress, and leisure activity.
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Lin, Sheng-Yi, i 林昇毅. "Forecasting Taiwan Stock Index Futures－An Application of Fuzzy Time Series". Thesis, 2000. http://ndltd.ncl.edu.tw/handle/54980588567474899201.
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碩士朝陽大學
財務金融系碩士班
88
In this study, the author investigates the relationship between TAIFEX Taiwan Stock Index Futures and SIMEX MSCI Taiwan Stock Index Futures after 2:45 p.m., and tries to employ traditional and fuzzy time series model to predict the price of Taiwan Stock Index Futures in testing period. Major empirical results are summarized as follows. 1.There exists a lead-lag relationship on daily price volatility between Taiwan Stock Index Futures and MSCI Taiwan Stock Index Futures, which reveals that the information flow is rapid. So, the informed trader can use the time lag between two markets to make a profit. 2.Using the daily price of MSCI Taiwan Stock Index Futures after 2:45 p.m. to forecast Taiwan Stock Index Futures, VAR model has better performance than AR model. Therefore, it is advantageous to forecast Taiwan Stock Index Futures by considering the daily price volatility of MSCI Taiwan Stock Index Futures after 2:45 p.m. 3.The performance of fuzzy time series is better than AR model. This could be that the trend volatility of the future price is not suitable for linear model.
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Lin, Hung-Chun, i 劉虹君. "Forecasting And Analyzing the Baltic Dry Index–Using Fuzzy Piecewise Regression". Thesis, 2006. http://ndltd.ncl.edu.tw/handle/49210267210339133469.
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碩士開南管理學院
航運與物流管理系碩士班
94
The global economic and trade is changing rapidly, which influence the freight at the shipping market. The bulk shipping takes the most part of shipping business in Taiwan. There are many factors influence the freight of bulk shipping, thus, the uncertainty is high, which attract researchers to study the fluctuate factors of the Baltic Dry Index. There are numerous factors influence the Baltic Dry Index (BDI), however, based on the related literature review, there are lack of related research. Besides, most of them short of overall analysis of the Baltic Dry Index. This research, therefore, tries to use four major influence factors which intriduct by Gray. The forecasting model mostly uses the tradition regression in this field, but it is unable to deal with outliers. This research utilizes the fuzzy piecewise regression analysis with automatic change-point detection to forecast Baltic Dry Index, to build the freight and rent development trends of the shipping market. The result of this study shows that the major factors influence Baltic Dry Index are the Oil price, second hand price of the Capesize ship, second hand price of the Panamax ship, new building price of the Panamax ship, the rent of time charter for Capesize, the rent of voyage charter for grain, and the rent of voyage charter for coal. Among these factors, the second hand price of the Capesize ship and new building price of the Panamax ship are the most important impact factor of the Baltic Dry Index. By using above-mentioned impact forecasting model, the instant Baltic Dry Index can be obtained, which provide the bulk operators a clear picture when considering the rent of the ship.
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Chen, Yu-Ti, i 陳郁迪. "The S&P 500 Index Forecasting by fuzzy ArtificialNeural Network". Thesis, 2013. http://ndltd.ncl.edu.tw/handle/79062768174588895553.
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碩士國立高雄海洋科技大學
電訊工程研究所
101
People are obliged to studying the topics of finance and investment on account of economic regressing, and rising prices in market in recent days. The investment in stock is one of the preferred choice for the modern finance. There are various data on forecasting the stock investment. The S&P500 Index is better tool for forecasting. The theme of this research is focusing S&P 500 Index forecasting, as the investor's reference data. S&P 500 (Standard & Poor's 500) index began in 1957 by the Standard & Poor's establishment. The U.S. stock market made an average record observed range up to top 500 U.S. listed companies since the year of 1957. S&P500 Index System use Back-propagation Neural Network and Echo State Networks as the tools to build up models. The goal is to predict the highest-price, lowest-price, and close price in the daily S&P 500 Index, and to add fuzzy rules in to Back-propagation Neural Network to improve the prediction. The result that by adding Fuzzy Rules into Back-propagation Neural Network can improve the learning and momentum effectively. This research categorize the prediction into two models. The result shows that stock price increase rapidly from 1995 to 2007. Therefore, this paper categorize S&P 500 into two models, one is trained between 1965-1990 and tested between 1995-2000, while another one is trained from 1995-2000 and tested from 2001-2007. By comparing the results, it indicates that by adding the Fuzzy Rules can lower down the variation between training and testing.
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Lin, Chung-yang, i 林濬洋. "Evaluating process performance based on capability index Cpm with fuzzy data". Thesis, 2010. http://ndltd.ncl.edu.tw/handle/28376910427767654478.
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碩士逢甲大學
工業工程與系統管理學研究所
98
Process capability indices are convenient and powerful tools for measuring process performance. However, the traditional crisp-based approach for estimating and testing process performance becomes inappropriate when the measurements of quality characteristic cannot be precisely recorded or determined. Thus, this study extends its applications to a fuzzy environment and constructs the membership function of fuzzy estimation of index Cpm based on the α-cut. A decision rule is developed for assessing process performance based on the relationship between the constructed membership function and rejection region. In addition, this study also applies fuzzy ranking method to compare the performance of several supplier processes and select a better supplier among them. Finally, a case study is presented to illustrate the applications of the proposed approach and provide a reference for assessing the capability of process when the measurements of quality characteristic cannot be precisely recorded or determined.
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WEN, CHUN-YI, i 溫鈞怡. "Two-Factor Fuzzy Hidden Markov Model For Stock Price Index Forecasting". Thesis, 2015. http://ndltd.ncl.edu.tw/handle/88881689512151945575.
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碩士明新科技大學
管理研究所碩士在職專班
103
An effective forecasting system can help companies or individuals to reduce investment risk. Existing research has proposed numerous ways to predict, and most of them strive for higher precision of prediction. In recent years, the hidden Markov model began to be applied to social science research, and proved to have excellent performance in predicting returns. To assess their empirical advantage, this study uses two-factor Hidden Markov Model to predict four stock indexes of daily trading information, including : Taiwan weighted stock index (for the period 1990-1999), the Nasdaq stock index (for the period 1990-1999), standard and poor's 500-stock index (for the period 2000-2009), and the Dow Jones industrial stock index (for the period 2000-2009). The empirical results show that our predictive models have better prediction performance of lower forecast errors than do many other existing models.
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CHEN, WEI, i 陳葦. "Apply Genetic Algorithm and Fuzzy Inference to Forecast Stock Price Index". Thesis, 2019. http://ndltd.ncl.edu.tw/handle/z2wk7j.
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碩士朝陽科技大學
財務金融系
107
In the present study, we explore the impact of company’s financial indicators on the companys stock price using the daily data drawn from the database of the Taiwan Economic Journal. Through employing fuzzy genetic algorithm, C4.5 decision tree and random forests, we investigate the relationship between company financial indicators and the companys stock price. We find that fuzzy genetic algorithm predicts an overall accuracy rate of 64.6% or more among them. The prediction accuracy of t on the TSMC’s stock price reached as high as 77.0% by using the fuzzy algorithm. The second best prediction for TSMCs is from the random forest. The accuracy rate is 65.5% overall. As for the prediction of Hon Hais stock price, the fuzzy genetic algorithm could have the highest accuracy rate of 64.6%. Therefore, it seems that the prediction accuracy of model would improve with fuzzifying the variables and the evolution of the genes. Furthermore, the volatility of the stock prices would have the impact on the accuracy of prediction model.
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Chen, Chiu-Ling, i 陳秋玲. "Using fuzzy theory to construct the index for attendants of catering industry". Thesis, 2014. http://ndltd.ncl.edu.tw/handle/b73x32.
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碩士義守大學
財務金融學系
102
Customer satisfaction is one of the serious issues of good services. Food industry should give priority to improving the quality of service in the highest impact on customer satisfaction and "Reliability" by E service processes and equipment, In addition to continuing to maintain existing service levels, it is more important to grasp market trends and consumer habits of people periodically. This study aims to construct a professional catering staff competence indicators. Firstly, based on the literature to explore the catering staff expertise, research expertise of the catering staff. Using Comprehensive analysis to know the of the connotation of catering staff ability . And according to the above induction to develop the index concept of professional competence for the restaurant waiter . Secondly, Correction and interpretation through fuzzy expert opinion of the Delphi Technique, will afford assistance to construct a catering waiter professional competence indicator. Finally, this research will give specific recommendations, as reference for catering staff and technical and vocational institutions. As for education units, Ability index system must be combined with learning evaluation. The primary purpose of evaluation is to confirm "in improving not proven ", and through the implementation of evaluation to make sure the (fitness) of indicators. In the evaluation process it should be in line with scientific and democratic process, put emphasis on process and results, as well as on formative and summative evaluation. Besides,keep tracking improvements after evaluation is important , too. Based on the findings and analysis, the conclusions as follows: First, this study established professional catering staff competence indicators into two dimensions, namely, basic skills and professional competence. Second, in the dimensions of the basic capabilities , its main targets are "the basis of academic ability," "self-management", "team life skills." Third, in the dimensions of professional competence, the main indicators are "professional knowledge and skills", "niche capabilities", "workplace capability", "dining etiquette." Based on this conclusion, I hope to be able to recommend some suggestions to restaurants educational authorities, teacher training institutions catering, catering and future faculty researchers.
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Hsu, Kai-chun, i 許楷均. "Estimating the Present Serviceability Index of Flexible Pavement using Fuzzy Regression Analysis". Thesis, 2008. http://ndltd.ncl.edu.tw/handle/54542688085831101361.
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碩士國立成功大學
土木工程學系碩博士班
96
The main objective of pavement construction is to provide the safe and comfortable quality of the road for users. The roughness of pavement is an important effect to the users’ feeling of the road. However, the pavement condition deteriorates because of traffic, rainfalls, temperature, etc. The estimation and maintanence of pavement condition domestically has some problems, for example lack of long-term pavement data, incompleted records, unprecise models etc. In conclusion, considering the relationship between deteriorated pavement condition and the users’ feeling of road, maintaining good pavement serviceability and predicting pavement condition are worthy subjects to research. In the past, conventional regression model often had been used in estimating pavement condition. For example, Carey and Irick in 1960 established PSI(Present Serviceability Index) regression model to deal with the relation between PSR (Present Serviceability Rating) and objective measurement(Chang et al, 2003). But PSR and other deteriorated pavement condition is evaluated by the subjective judgment. The conventional regression model cannot deal with uncertainty and fuzziness data ,so fuzzy regression model is used to establish the PSI regression model and handle this kind of problems. This study aims at disscussing the relationship between PSR and the deteriorated pavement and applying Pan and Hwang’s fuzzy regression model in 2008 to develop fuzzy PSI(Present Serviceability Index) regression model. This model can deal with the fuzzy dependent parameters and fuzzy/crisp independent parameters. Based on the result of this study, roughness affect pavement serviceability mostly and manholes affect secondly. Therefore, this fuzzy regression model in this study has 70% explained the ability in relationship between PSR and the deteriorated pavement condition through R-square. It can help pavement managers to estimate pavement serviceability effectively and order suitable pavement maintenance strategies.
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Hsu, Yu-Wei, i 許祐偉. "A Multivariate Fuzzy Time Series Model to Forecast Stock Index in Taiwan". Thesis, 2006. http://ndltd.ncl.edu.tw/handle/25335919311480705927.
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碩士逢甲大學
企業管理所
94
After the definition of fuzzy time series being proposed, different models were developed subsequently. Most models considered the forecasted target as the only one variable for forecasting. However, Huarng (2001) proposed the heuristic models, which found that the introducing of other variables (namely heuristic variables) can improve the forecasting results of fuzzy time series. According to Huarng’s model, this study proposes a Multivariate Heuristic Model. The model illustrates how to determine the thresholds, how to define the rules for each heuristic variable, how to judge the comprehensive influence of mutivariable and how to select proper fuzzy sets,etc. Furthermore, the model can transfer the fuzzy time series into a multivariable structure and avoiding complicated calculations. In addition, this study applies the Multivariate Heuristic Model to forecast Taiwan Stock Exchange Capitalization Weighted Stock Index. In addition to the stock index, we also choose three different heuristic variables, NASDAQ, Dow Jones, and M1b of Taiwan. Two different empirical analyses are conducted respectively based on single heuristic variables and two heuristic variables. The empirical results show: 1. The heuristic models outperfoems the models without. It means that the application of the multivariate heuristic model can really improve the forecasting results. 2. The forecasting performance of two heuristic variables is better than the single heuristic variable. It means that there will be better forecasting results when more heuristic variables are applied.
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He, Jyun-Sian, i 何俊賢. "Improved Fuzzy C-Means Algorithm with Hierarchical Structure and Cluster Validity Index". Thesis, 2010. http://ndltd.ncl.edu.tw/handle/72455056801854029071.
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碩士國立東華大學
電機工程學系
98
In the traditional fuzzy c-means algorithm, the Euclidean distance function is used to calculate the membership value of a data point for each data cluster, and the initialized cluster centers are randomly assigned. Hence, the clustering results often obtain bad results caused by some data sets and it is easier to fall into the local optimal solution. An improved algorithm is proposed in this thesis for dealing with the problems mentioned above. In the proposed algorithm, the hierarchical single linkage cluster method is used to obtain the initial cluster centers in order to modify the uncertain factor of random initial setting problem. In order to deal with the inadequate problem of Euclidean distance, the Mahalanobis distance is used to calculate the update equation of the membership matrix based on the character of its adjusting covariance matrix according to the tendency of data. Thus, the proposed method can improve the correctness compared with the traditional fuzzy c-means algorithm. Finally, the clustering validity index is also used in the proposed algorithm to identify the optimal number of clusters. The experiment results in this thesis show that the proposed algorithm can divide the data sets into proper clusters, and the cluster results are more correct than other cluster method.