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Rozprawy doktorskie na temat „Fuzzy analysis”

Autor: Grafiati

Data publikacji: 4 czerwca 2021

Data aktualizacji: 25 lipca 2025

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1

Karim, Ehsanul, Sri Phani Venkata Siva Krishna Madani, and Feng Yun. "Fuzzy Clustering Analysis." Thesis, Blekinge Tekniska Högskola, Sektionen för ingenjörsvetenskap, 2010. http://urn.kb.se/resolve?urn=urn:nbn:se:bth-2165.

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The Objective of this thesis is to talk about the usage of Fuzzy Logic in pattern recognition. There are different fuzzy approaches to recognize the pattern and the structure in data. The fuzzy approach that we choose to process the data is completely depends on the type of data. Pattern reorganization as we know involves various mathematical transforms so as to render the pattern or structure with the desired properties such as the identification of a probabilistic model which provides the explaination of the process generating the data clarity seen and so on and so forth. With this basic sch

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2

Drobics, Mario. "Data analysis using fuzzy expressions /." Linz : Trauner, 2005. http://aleph.unisg.ch/hsgscan/hm00166742.pdf.

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Chan, Chee Seng. "Fuzzy qualitative human motion analysis." Thesis, University of Portsmouth, 2008. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.494009.

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Human motion analysis is a very important task for computer vision with a spectrum of potential applications. This thesis presents a novel approach to the problem of human motion understanding. The main contribution of the thesis is that fuzzy qualitative description has been developed for studying human motion from image sequences.

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Yamazaki, Tsukasa. "An improved algorithm for a self-organising controllerd its experimental analysis." Thesis, Queen Mary, University of London, 1992. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.320959.

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Reynolds, Robert. "Gene Expression Data Analysis Using Fuzzy Logic." Fogler Library, University of Maine, 2001. http://www.library.umaine.edu/theses/pdf/REynoldsR2001.pdf.

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Conroy, Justin Anderson. "Analysis of adaptive neuro-fuzzy network structures." Thesis, Georgia Institute of Technology, 2000. http://hdl.handle.net/1853/19684.

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Popoola, Ademola Olayemi. "Fuzzy-wavelet method for time series analysis." Thesis, University of Surrey, 2006. http://epubs.surrey.ac.uk/804949/.

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Merilan, Jean Elizabeth 1962. "The Use of Fuzzy Analysis in Epidemiology." Diss., The University of Arizona, 1996. http://hdl.handle.net/10150/565573.

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De, Maio Carmen. "Fuzzy concept analysis for semantic knowledge extraction." Doctoral thesis, Universita degli studi di Salerno, 2012. http://hdl.handle.net/10556/1307.

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2010 - 2011<br>Availability of controlled vocabularies, ontologies, and so on is enabling feature to provide some added values in terms of knowledge management. Nevertheless, the design, maintenance and construction of domain ontologies are a human intensive and time consuming task. The Knowledge Extraction consists of automatic techniques aimed to identify and to define relevant concepts and relations of the domain of interest by analyzing structured (relational databases, XML) and unstructured (text, documents, images) sources. Specifically, methodology for knowledge extraction defined in t

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10

Glodeanu, Cynthia Vera. "Conceptual Factors and Fuzzy Data." Doctoral thesis, Saechsische Landesbibliothek- Staats- und Universitaetsbibliothek Dresden, 2013. http://nbn-resolving.de/urn:nbn:de:bsz:14-qucosa-103775.

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With the growing number of large data sets, the necessity of complexity reduction applies today more than ever before. Moreover, some data may also be vague or uncertain. Thus, whenever we have an instrument for data analysis, the questions of how to apply complexity reduction methods and how to treat fuzzy data arise rather naturally. In this thesis, we discuss these issues for the very successful data analysis tool Formal Concept Analysis. In fact, we propose different methods for complexity reduction based on qualitative analyses, and we elaborate on various methods for handling fuzzy data.

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Touz'e, Patrick A. "Applications of fuzzy logic to mechanical reliability analysis /." This resource online, 1993. http://scholar.lib.vt.edu/theses/available/etd-03142009-040345/.

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12

Wang, Yanfei. "Fuzzy methods for analysis of microarrays and networks." Thesis, Queensland University of Technology, 2011. https://eprints.qut.edu.au/48175/1/Yanfei_Wang_Thesis.pdf.

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Bioinformatics involves analyses of biological data such as DNA sequences, microarrays and protein-protein interaction (PPI) networks. Its two main objectives are the identification of genes or proteins and the prediction of their functions. Biological data often contain uncertain and imprecise information. Fuzzy theory provides useful tools to deal with this type of information, hence has played an important role in analyses of biological data. In this thesis, we aim to develop some new fuzzy techniques and apply them on DNA microarrays and PPI networks. We will focus on three problems: (1) c

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13

Raghfar, Hossein. "Application of fuzzy set theory to poverty analysis." Thesis, University of Essex, 2001. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.343582.

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Touzé, Patrick A. "Applications of fuzzy logic to mechanical reliability analysis." Thesis, Virginia Tech, 1993. http://hdl.handle.net/10919/41583.

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15

Saboo, Jai Vardhan. "An investment analysis model using fuzzy set theory." Thesis, Virginia Polytechnic Institute and State University, 1989. http://hdl.handle.net/10919/50087.

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Traditional methods for evaluating investments in state-of-the-art technology are sometimes found lacking in providing equitable recommendations for project selection. The major cause for this is the inability of these methods to handle adequately uncertainty and imprecision, and account for every aspect of the project, economic and non-economic, tangible and intangible. Fuzzy set theory provides an alternative to probability theory for handling uncertainty, while at the same time being able to handle imprecision. It also provides a means of closing the gap between the human thought process an

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16

Wang, Yu. "Fuzzy clustering models for gene expression data analysis." Thesis, Northumbria University, 2014. http://nrl.northumbria.ac.uk/21438/.

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With the advent of microarray technology, it is possible to monitor gene expression of tens of thousands of genes in parallel. In order to gain useful biological knowledge, it is necessary to study the data and identify the underlying patterns, which challenges the conventional mathematical models. Clustering has been extensively used for gene expression data analysis to detect groups of related genes. The assumption in clustering gene expression data is that co-expression indicates co-regulation, thus clustering should identify genes that share similar functions. Microarray data contains plen

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17

Pao-Tan, Wang, and 王保丹. "Fuzzy Reliability Analysis." Thesis, 2000. http://ndltd.ncl.edu.tw/handle/68604522675022530624.

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碩士<br>中原大學<br>數學系<br>88<br>In the reliability theory, studies always focus on the states of system and its components under nonfuzzy(crisp) situation (see [1, 2, 7, 9]). Since Zadeh proposed the idea of fuzzy sets in 1965, the reliability theory in fuzzy environment has been studied (see [5, 6, 8, 10]). In this thesis we explore fuzzy-state structure functions and its possibility reliability by the Zadeh`s extension principle with triangular fuzzy numbers. First we review definitions and properties of coherent systems and its reliability functions. Then we propose coherent system

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18

Liao, Wen-Du, and 廖文督. "Fuzzy Portfolio Analysis with FuzzyReturns and Fuzzy InvestmentProportion." Thesis, 2011. http://ndltd.ncl.edu.tw/handle/53063367115813079879.

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碩士<br>淡江大學<br>管理科學研究所碩士班<br>99<br>In this paper, the fuzzy portfolio will be discussed due to uncertainty of proportion invested in each selected security in a portfolio. The paper will discuss how to solve the portfolio problem about investment proportion of each selected security based on possibilistic mean-standard deviation models. Then, the uncertain investment proportion of each chosen security in the portfolio will be regarded as a fuzzy number and also be formulated and proposed in this paper, showing how the portfolio selection problem will be solved. Finally, a numerical example of a

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19

Wang, Shinn-Wen, and 王信文. "Optimization of Fuzzy System by Fuzzy Clustering Analysis." Thesis, 1996. http://ndltd.ncl.edu.tw/handle/91650923483074530257.

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碩士<br>大葉工學院<br>電機工程研究所<br>84<br>Optimization of Fuzzy System by Fuzzy Clustering Analysis ABSTRACT Fuzzy rule base and fuzzy membership functions(MFs) are two major factors in deciding the performance of fuzzy inference system. Therefore, the design plays an important role for the performance stated above. Trial and error was usually the way to solution, which was not only costly and time-consuming but also promised no optimized result. In

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20

Wen, Jee-Chean, and 溫志群. "Stability Analysis of Fuzzy System and Fuzzy Perturbed System." Thesis, 2000. http://ndltd.ncl.edu.tw/handle/62340473891519384768.

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碩士<br>義守大學<br>電子工程學系<br>88<br>Stability is the main requirement of control system designs. Fuzzy control system should meet the requirement, too. We will discuss the stability of Takagi-Sugeno fuzzy model. System identification is the most important process to an unknown system. So, to identify a fuzzy model is the first thing we have to do. We discuss the stability analysis and design technique of fuzzy control system using fuzzy block diagram method, and obtain a sufficient condition to guarantee the stability of fuzzy nominal system by Lyapunov stability equation. When practical

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21

黃聖芫. "The comparison of gaussian fuzzy numbers and triangular fuzzy analysis." Thesis, 2003. http://ndltd.ncl.edu.tw/handle/75157544660722738259.

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Chen, Chien Hung, and 陳建宏. "Fuzzy Regression Analysis and Application of Interval Fuzzy Random Variables." Thesis, 2008. http://ndltd.ncl.edu.tw/handle/03996291397162071325.

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碩士<br>國立政治大學<br>應用數學研究所<br>97<br>The aim of this paper is to discuss the linear correspondance between two interval fuzzy random variables. We construct the regression equations of the upper and lower bounds of some interval fuzzy random variables, respectively, by the least squares. The upper and lower bounds of the estimated interval fuzzy random variables are derived by the regression equations of upper and lower bounds, respectively. The collected upper and lower bounds are all crisp data, not fuzzy ones. In this paper, the interval fuzzy random variables discussed are constructed by crisp

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23

CHEN, JIAN-LIANG, and 陳建良. "study of application of fuzzy cluster and fuzzy discriminant analysis." Thesis, 1992. http://ndltd.ncl.edu.tw/handle/78498594847952053296.

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STASI, SERENELLA. "LA LOGICA FUZZY NELLA RICERCA SOCIALE CON PARTICOLARE ATTENZIONE ALLE SCALE DI ATTEGGIAMENTO." Doctoral thesis, 2011. http://hdl.handle.net/11573/917150.

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Yang, Jia-Chi O., and 歐陽嘉麒. "Analysis of Fuzzy Time Series." Thesis, 2001. http://ndltd.ncl.edu.tw/handle/11173549469127417428.

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碩士<br>國立清華大學<br>工業工程與工程管理學系<br>89<br>Fuzzy Sets Theory was introduced by L. A. Zadeh in 1965. Up to now, fuzzy sets have been applied to many fields such as Decision Analysis, System Theory, Artificial Intelligence, Economics and Control Theory. However, until 1993, Q. Song and B.S Chissom proposed a fuzzy time series method which provides an alternative approach for some special dynamic process. This paper presents two methods to forecast secular trend and seasonal variation time series problems respectively. The revised fuzzy time series method uses Song and Chissom’s first-order

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26

Tseng, Chun-Shu, and 曾淳煦. "Analysis for Fuzzy Mathematical Programming." Thesis, 1993. http://ndltd.ncl.edu.tw/handle/54827731249729679157.

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碩士<br>大同大學<br>電機工程研究所<br>81<br>In this thesis, the main goal is to analyze the fuzzy mathematical programming and how to apply it in an optimal problem. In the fuzzy mathematical programming, it included symmetrical model and nonsymmetrical model. Otherwise, we use the duality property of the fuzzy mathematical programming problems for transferring a difficult solving problem to easy. Next, in this thesis, we proposed a general form of fuzzy numbers. Then using this general form, we can rewrite the problem with no fuzzy components by different kinds of fuzzy index. Finally, when there exist un

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27

Lertworasirikul, Saowanee. "Fuzzy Data Envelopment Analysis (DEA)." 2002. http://www.lib.ncsu.edu/theses/available/etd-05032002-101350/unrestricted/etd.pdf.

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Lin, Nancy Pei-ching, and 林丕靜. "Correlation Analysis of Fuzzy Sets." Thesis, 1998. http://ndltd.ncl.edu.tw/handle/04600114630994536322.

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Jha, Devendra. "Fuzzy approaches for image analysis." Thesis, 2003. http://localhost:8080/xmlui/handle/12345678/5556.

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呂國忠. "Fuzzy Decision Making Analysis -- Evaluating Weapon Systems Using Ranking Fuzzy Number." Thesis, 1998. http://ndltd.ncl.edu.tw/handle/23131979699426093959.

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碩士<br>國防管理學院<br>資源管理研究所<br>86<br>In this paper, we modify Chen''s evaluating model and Hwang''s relative distance method to propose a new algorithm. That is, we develop a general and new method for evaluating weapon system, which use nine scales concepts of AHP and combine the triangular fuzzy numbers to represent fuzzy performance of the corresponding to each attribute, and establish fuzzy judgement matrix by total score of performance. Then take fuzzy number 1, 3, 5, 7, 9 to denote the weight for each attribute. Last, use ranking fuzzy numbers to evaluating the optimal alternative. For p

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Shun, Lin Tsu, and 林子舜. "On Fuzzy Laest-Square Regression Analysis for Fuzzy Input-Output Data." Thesis, 1997. http://ndltd.ncl.edu.tw/handle/26252701230272832734.

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碩士<br>中原大學<br>數學研究所<br>86<br>In the fuzzy linear regression model , studies were focus on the output and parameters as fuzzy numbers, and the input as nonfuzzy real numbers. One ofthese fuzzy linear regression analyses is Tanaka linear programming method and the other is the least square method. Tanaka method is to consider the fuzziness of models and then transform the method of parameter estimate into linear programming method. Least square method is to define the distance between two fuzzy numbers, and then define a least square objective function. Moreover, the concept of noise cluster is

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Cai, Hao Xu, and 蔡皓旭. "Interval regression analysis with fuzzy data." Thesis, 2016. http://ndltd.ncl.edu.tw/handle/48136091858014961077.

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碩士<br>國立政治大學<br>應用數學系<br>104<br>Objective: This study concerns how to develop effective fuzzy regression models. In the literature, little is addressed on how to evaluate the effectiveness of fuzzy regression models developed with different regression methods. We consider this issue in this work and present a framework for such evaluation. Method: We consider fuzzy regression models developed with different regression approaches. A method to evaluate the developed models is proposed. We then show that the proposed method possesses desirable mathematical properties and it is applied to compare

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Chang, Shih-Da, and 張世達. "Fuzzy Logic System Analysis and Applications." Thesis, 2009. http://ndltd.ncl.edu.tw/handle/53727799037537521001.

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LEE, SHENG-EN, and 李聖恩. "USING FUZZY CLASSIFIER FOR SCENE ANALYSIS." Thesis, 1996. http://ndltd.ncl.edu.tw/handle/44259067115352878850.

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Liu, Man Jun, and 劉曼君. "On Possibility Analysis For Fuzzy Data." Thesis, 1995. http://ndltd.ncl.edu.tw/handle/37394476899461085668.

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碩士<br>中原大學<br>應用數學研究所<br>83<br>Although there are many researches on statistical analysis for fuzzy data, there are less discussions on possibility analysis for fuzzy data. In this thesis, our goal is to construct a possibility space for the analysis of fuzzy data. Especially we propose the so-called double fuzzy variable. What is " possibility "? Zadeh proposed the concept of fuzzy sets. Then there are two types of description for the uncertainty : one with randomness, the other with fuzzi

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Ko, Cheng Hsiu, and 柯政秀. "On Cluster-Wise Fuzzy Regression Analysis." Thesis, 1994. http://ndltd.ncl.edu.tw/handle/42995305129031859293.

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碩士<br>中原大學<br>應用數學研究所<br>82<br>Since Tanaka et al. proposed a study in linear regression analysis with fuzzy model, fuzzy regression analysis has been widely studied and applied in a variety of substantive areas. We know that the regression analysis in the case of heterogeneity of observations are commonly presented in practice. In this paper, the main goal is to apply fuzzy clustering techniques to fuzzy regression analysis. The fuzzy clustering is used to overcome the heterogeneous proble

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Ruey-Chyn, Tsaur, and 曹銳勤. "MODELING AND ANALYSIS in FUZZY REGRESSIONS." Thesis, 1999. http://ndltd.ncl.edu.tw/handle/72502514904086592087.

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博士<br>國立清華大學<br>工業工程與工程管理學系<br>87<br>ABSTRACT Fuzzy regression was first introduced by Tanaka et al [30] in 1982 to be an alternative to evaluate the relation between input variables and output variable. According to the simulation results proposed by Kim, Moskowitz and Koksalan showed that the predicted performance in statistical regression is better than fuzzy regression when the collected data is large. However, fuzzy regression performance becomes relative better as the size of data set diminished and the aptness of the regression model deteriorated. Since fuzzy reg

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Yang, Shi-Qi, and 楊士奇. "Decision Analysis of Fuzzy Project Scheduling." Thesis, 1996. http://ndltd.ncl.edu.tw/handle/71800983468662193513.

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Liu, Hsien-Hsiung, and 劉賢雄. "Data Analysis of Conical Fuzzy Vectors." Thesis, 1996. http://ndltd.ncl.edu.tw/handle/79340169041450710266.

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Wang, Chih Shioung, and 王志雄. "Fuzzy Analysis of a Competence Set." Thesis, 1994. http://ndltd.ncl.edu.tw/handle/88711028479721416440.

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碩士<br>國立清華大學<br>工業工程研究所<br>82<br>Competence set, which is a Habitual Domain (HD), is a collection of knowledge, idea, and skills. When we face a problem, we use these knowledge, idea and skills to help us to solve the problem. Over time unless we pay special effort to acquire new knowledge, our competence set will be stablized in a certain domain. When we face a problem which beyonds our current competence set (CS), how can we expand our CS effectively so that we can solve the problem effe

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Manna, Sukanya. "Evidence based fuzzy single document analysis." Phd thesis, 2010. http://hdl.handle.net/1885/150610.

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Human beings can extract meaningful information from single documents and can even summarize them depending on their interest. Computers on the other hand are used in increasingly large number of documents to process them. Even with vast number of documents we are drowning in, there will always be need of important documents which occur singly or in small numbers. For example, it is unlikely that a statistically significant number of airplanes will collide with tall buildings. So, to analyze and extract significant information from reports or documents related to this kind of scenario, it requ

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黃大偉. "Event Tree Analysis Using Fuzzy Concept." Thesis, 1997. http://ndltd.ncl.edu.tw/handle/11517306333510215915.

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碩士<br>國立清華大學<br>工業工程研究所<br>85<br>Event tree analysis (ETA) method is a straightforward and simple approach for risk assessment. It can be used to identify various sequences and their causes, and also to give the analyst the clear picture about which top event dominates the safety of the system. The traditional ETA uses a single probability to represent each top event. However, it is unreasonable to evaluate the occurrence of an event by using a crisp value without considering the inherent uncertainty and imprecision a state has. Since fuzzy set theory provides a framework for dealing with

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Rau, Min-Zong, and 饒旻宗. "Fuzzy Clustering with Principal Component Analysis." Thesis, 2010. http://ndltd.ncl.edu.tw/handle/98871081495872381063.

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碩士<br>國立中山大學<br>電機工程學系研究所<br>98<br>We propose a clustering algorithm which incorporates a similarity-based fuzzy clustering and principal component analysis. The proposed algorithm is capable of discovering clusters with hyper-spherical, hyperellipsoidal, or oblique hyper-ellipsoidal shapes. Besides, the number of the clusters need not be specified in advance by the user. For a given dataset, the orientation, locations, and the number of clusters obtained can truthfully reflect the characteristics of the dataset. Experimental results, obtained by running on datasets generated synthetically, sh

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He, Guan-Sian, and 何冠賢. "Stability Analysis of Polynomial Fuzzy Systems." Thesis, 2012. http://ndltd.ncl.edu.tw/handle/76065397030027969171.

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碩士<br>國立中正大學<br>光機電整合工程研究所<br>100<br>This study presents a polynomial fuzzy model and a path controller design for a nonlinear four-wheeled omnidirectional mobile robot (ODMR) using polynomial fuzzy systems. A polynomial controller was designed according to the parallel distributed compensation (PDC) from the given polynomial fuzzy model of the ODMR. This proposed controller is capable of driving the closed-loop system states of the ODMR to follow reference trajectory commands. We used stability conditions that were represented by the sum of squares (SOS) to guarantee global stability. 　In add

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Shie, Yi Ting, and 謝逸婷. "Using Fuzzy Ranking Analysis in Data Envelopment Analysis models." Thesis, 2005. http://ndltd.ncl.edu.tw/handle/37817448927487285064.

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碩士<br>南台科技大學<br>工業管理研究所<br>93<br>The Data Envelopment Analysis (DEA) was a methodology to measure the relative efficiency of the decision making units (DMUs) with the same input and output items. Since 1978, Charnes, Cooper and Rhodes proposed DEA method, many researchers were engaged in related researches. Traditionally, the coefficients of DEA models were assumed to be crisp values. However, it was invalid in some cases. Based on Zadeh’s fuzzy theory, some researchers developed the fuzzy DEA (FDEA). This paper is intended to give an another approach to FDEA model. First of all, we

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Wei, Shih-Hua, and 魏世驊. "New Methods for Fuzzy Risk Analysis Based on Similarity Measures between Fuzzy Numbers." Thesis, 2007. http://ndltd.ncl.edu.tw/handle/am43ea.

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碩士<br>國立臺灣科技大學<br>資訊工程系<br>95<br>In recent years, the task of measuring the degree of similarity between fuzzy numbers plays an important role in fuzzy decision making, information fusion and fuzzy risk analysis. In this thesis, we present two similarity measures for generalized fuzzy numbers and interval-valued fuzzy numbers. It combines the concepts of geometric distance, the perimeter, height and center of gravity point of generalized fuzzy numbers and interval-valued fuzzy number, respectively. Moreover, we also presented an interval-valued fuzzy number adjusting algorithm. Based on propos

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(9863570), J. Zajaczkowski. "Analysis of the hierarchical fuzzy control using evolutionary algorithms." Thesis, 2010. https://figshare.com/articles/thesis/Analysis_of_the_hierarchical_fuzzy_control_using_evolutionary_algorithms/13462052.

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"The research presented in this thesis examines the construction of a fuzzy logic controller for complex nonlinear system by control system decomposition into hierarchial fuzzy logic subsystems ... evolutionary algorithm (EA) based methods are proposed to determine the control system for the hieracrchical fuzzy system (HFS)"--Abstract.

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Lee, Sheng-Wei, and 李昇威. "Study and Analysis of Fuzzy Time Series." Thesis, 2010. http://ndltd.ncl.edu.tw/handle/642ufe.

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碩士<br>國立臺北教育大學<br>數學暨資訊教育學系(含數學教育碩士班)<br>98<br>Since Song proposed fuzzy time series model – hypothesis on the undefined time series, in 1993, many scholars have come up with related research, and they got good results. In this study, I used fuzzy time series to predict the number of special education students – through the method that S.R. Singh (2007), Hwang (1998), and Ching-Hsue Cheng (2009) proposed. I used three interval quantity to predict the three methods, and used MSE(Mean Square Error) and M APE(Mean Absolute Percent Error) to check the accuracy of the prediction. They indicate the

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Lo, Chien-Chih, and 羅堅秩. "Fuzzy Linear Modeling for Load Characteristics Analysis." Thesis, 1999. http://ndltd.ncl.edu.tw/handle/51368262719104230250.

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碩士<br>國立海洋大學<br>電機工程學系<br>87<br>Load characteristics are most important information of a power system and of which the analysis is a critical task for a utility company. The main purpose of this project is to investigate the application of fuzzy modeling to the analysis of load characteristics. The method of fuzzy modeling is suitable for the analysis of load characteristics due to the inherent nonlinearity of load curves. A fuzzy model is a set of fuzzy IF-THEN rules for describing system behaviors.This thesis constructs fuzzy load models based on measured load data to set up the

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Xu, Jia Yuan, and 許嘉元. "Fuzzy analysis and forecasting in time series." Thesis, 1994. http://ndltd.ncl.edu.tw/handle/02051032700206938986.

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