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Dissertations / Theses on the topic 'Fuzzy model identification'

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Published: 3 June 2025

Last updated: 31 July 2025

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1

Franco, Ivan Carlos 1976. "Controle preditivo baseado em modelo neuro-fuzzy de sistemas não-lineares aplicado em sistema de refrigeração = Model predictive control based on neuro-fuzzy nonlinear systems applied to a refrigeration plant." [s.n.], 2012. http://repositorio.unicamp.br/jspui/handle/REPOSIP/266817.

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Orientador: Flávio Vasconcelos da Silva<br>Tese (doutorado) - Universidade Estadual de Campinas, Faculdade de Engenharia Química<br>Made available in DSpace on 2018-08-20T15:14:24Z (GMT). No. of bitstreams: 1 Franco_IvanCarlos_D.pdf: 30656846 bytes, checksum: 73b0216f94ce7393fb51d78cc6e4ea7f (MD5) Previous issue date: 2012<br>Resumo: Os sistemas de refrigeração estão presentes em diferentes ramos da indústria e caracterizam-se como grandes consumidores de energia com considerável comportamento não-linear. Inúmeros trabalhos vêm sido desenvolvidos para promover a redução dos gastos energético

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Mitchell, Ryan. "A WANFIS Model for Use in System Identification and Structural Control of Civil Engineering Structures." Digital WPI, 2012. https://digitalcommons.wpi.edu/etd-theses/1165.

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With the increased deterioration of infrastructure in this country, it has become important to find ways to maintain the strength and integrity of a structure over its design life. Being able to control the amount a structure displaces or vibrates during a seismic event, as well as being able to model this nonlinear behavior, provides a new challenge for structural engineers. This research proposes a wavelet-based adaptive neuro- fuzzy inference system for use in system identification and structural control of civil engineering structures. This algorithm combines aspects of fuzzy logic theory,

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Lima, Nádson Murilo Nascimento. "Modelagem e controle hibrido preditivo por logica fuzzy de processos de polimerização." [s.n.], 2006. http://repositorio.unicamp.br/jspui/handle/REPOSIP/266795.

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Orientador: Rubens Maciel Filho<br>Dissertação (mestrado) - Universidade Estadual de Campinas, Faculdade de Engenharia Quimica<br>Made available in DSpace on 2018-08-09T11:12:44Z (GMT). No. of bitstreams: 1 Lima_NadsonMuriloNascimento_M.pdf: 1887705 bytes, checksum: e0761ce0e30dd05a47c9cfbe9b0968ef (MD5) Previous issue date: 2006<br>Resumo: A síntese de controladores representa uma importante vertente dos desenvolvimentos atuais no campo da pesquisa acadêmica e industrial. Um controlador bem projetado pode significar sucesso no que se refere aos objetivos de produção, sendo gerados materiais

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Jesse, Alexandra. "Towards a lexical fuzzy logical model of perception : the time-course of information in lexical identification of face-to face speech /." Diss., Digital Dissertations Database. Restricted to UC campuses, 2005. http://uclibs.org/PID/11984.

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5

Obut, Salih. "Control Of Ph In Neutralization Reactor Of A Waste Water Treatment System Using Identification Reactor." Master's thesis, METU, 2005. http://etd.lib.metu.edu.tr/upload/2/12606395/index.pdf.

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A typical wastewater effluent of a chemical process can contain several strong acids/bases, weak acids/bases as well as their salts. They must be neutralized before being discharged to the environment in order to protect aquatic life and human welfare. However, neutralization process is highly non&ndash<br>linear and has time&ndash<br>varying characteristics. Therefore, the control of pH is a challenging problem where advanced control strategies are often considered. In this study, the aim is to design a pH control system that will be capable of controlling the pH-value of a plant waste-water

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Alvarado, Christiam Segundo Morales. "Estudo e implementação de métodos de validação de modelos matemáticos aplicados no desenvolvimento de sistemas de controle de processos industriais." Universidade de São Paulo, 2017. http://www.teses.usp.br/teses/disponiveis/3/3139/tde-05092017-092437/.

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A validação de modelos lineares é uma etapa importante em um projeto de Identificação de Sistemas, pois a escolha correta do modelo para representar a maior parte da dinâmica do processo, dentro de um número finito de técnicas de identificação e em torno de um ponto de operação, permite o sucesso no desenvolvimento de controladores preditivos e de controladores robustos. Por tal razão, o objetivo principal desta Tese é o desenvolvimento de um método de validação de modelos lineares, tendo como ferramentas de avaliação os métodos estatísticos, avaliações dinâmicas e análise da robustez do model

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Godoy, Andre Pereira de. "Modelagem de processos de acumulação de biomassa e de açucar da cana-de açucar via sistemas nebulosos." [s.n.], 2007. http://repositorio.unicamp.br/jspui/handle/REPOSIP/259127.

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Orientadores: Gilmar Barreto, Ginalber Luiz de Oliveira Serra<br>Dissertação (mestrado) - Universidade Estadual de Campinas, Faculdade de Engenharia Eletrica e de Computação<br>Made available in DSpace on 2018-08-09T18:49:20Z (GMT). No. of bitstreams: 1 Godoy_AndrePereirade_M.pdf: 5878897 bytes, checksum: e24b9a4ace4612b1e7cc56ccc677932f (MD5) Previous issue date: 2007<br>Resumo: Este estudo objetiva identificar e ajustar um modelo nebuloso (Fuzzy) para a predição de um passo a frente dos processos de acumulação de biomassa e de açúcar da cana-de-açúcar com índices de erro inferiores aos obt

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Machado, Jeremias Barbosa. "Modelagem e controle preditivo utilizando multimodelos." [s.n.], 2007. http://repositorio.unicamp.br/jspui/handle/REPOSIP/259984.

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Orientadores: Wagner Caradori do Amaral, Ricardo Jose Grabrielli Barreto Campello<br>Dissertação (mestrado) - Universidade Estadual de Campinas, Faculdade de Engenharia Eletrica e de Computação<br>Made available in DSpace on 2018-08-09T14:19:44Z (GMT). No. of bitstreams: 1 Machado_JeremiasBarbosa_M.pdf: 6477617 bytes, checksum: 3f0c4fec476306e8cc05a7940894b0a0 (MD5) Previous issue date: 2007<br>Resumo: o interesse na utilização de algoritmos de controle sofisticados cresce no meio industrial devido à necessidade de melhor qualidade dos produtos produzidos. Uma abordagem que vem ganhando dest

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9

Hu, Cheng Lin. "Design optimization of fuzzy models in system identification." Thesis, University of Macau, 2010. http://umaclib3.umac.mo/record=b2493501.

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Grisales, Palacio Victor Hugo. "Modélisation et commande floues de type Takagi-Sugeno appliquées à un bioprocédé de traitement des eaux usées." Phd thesis, Université Paul Sabatier - Toulouse III, 2007. http://tel.archives-ouvertes.fr/tel-00136382.

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Ce travail de thèse s'inscrit au carrefour de l'Automatique, de l'Intelligence Artificielle et des Biotechnologies. Il cherche à développer une méthodologie de modélisation et de commande qui repose sur une approche par logique floue. La première partie du travail présente une introduction aux principes et techniques mises en Suvre dans les stations d'épuration actuelles, et met en évidence la difficulté de modélisation des différents phénomènes mis en jeu. A partir de ce constat, dans une deuxième partie, focalisée sur la modélisation et la commande floues, nous développons d'abord l'identifi

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Renners, Ingo. "Data-driven system identification via evolutionary retrieval of Takagi-Sugeno fuzzy models." [S.l. : s.n.], 2004. http://deposit.ddb.de/cgi-bin/dokserv?idn=974452351.

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Huang, Fei. "Contributions à l'élaboration des modèles à partir de données pour l'estimation de la durée de vie résiduelle des roulements." Electronic Thesis or Diss., Université de Lorraine, 2020. http://www.theses.fr/2020LORR0019.

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Cette thèse de doctorat porte sur l’estimation de la durée de vie résiduelle d’un roulement sur la base des signatures obtenues à partir des signaux de vibration collectés pour un nombre restreint de roulements identiques durant un cycle complet de fonctionnement. Nous avons élaboré de nouvelles signatures qui ont une évolution monotone croissante avec l’état de dégradation des roulements et nous avons proposé un modèle d’estimation de la durée de vie résiduelle des roulements, basé sur un système d’inférence floue. Les paramètres du modèle sont identifiés par apprentissage à partir d’une peti

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Zaidi, Salman [Verfasser]. "System Identification of Stochastic Nonlinear Dynamic Systems using Takagi-Sugeno Fuzzy Models / Salman Zaidi." Kassel : Kassel University Press, 2019. http://d-nb.info/118450279X/34.

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Rodrigues, Marconi C?mara. "Identifica??o fuzzy-multimodelos para sistemas n?o lineares." Universidade Federal do Rio Grande do Norte, 2010. http://repositorio.ufrn.br:8080/jspui/handle/123456789/15143.

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Made available in DSpace on 2014-12-17T14:54:55Z (GMT). No. of bitstreams: 1 MarconiCR_TESE.pdf: 2377871 bytes, checksum: c798a5eab76defef17ac0fe081e2453d (MD5) Previous issue date: 2010-03-16<br>Coordena??o de Aperfei?oamento de Pessoal de N?vel Superior<br>This paper presents a new multi-model technique of dentification in ANFIS for nonlinear systems. In this technique, the structure used is of the fuzzy Takagi-Sugeno of which the consequences are local linear models that represent the system of different points of operation and the precursors are membership functions whose adjustments ar

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Thiaw, Lamine. "Identification de systèmes dynamiques non linéaires par réseaux de neurones et multimodèles." Phd thesis, Université Paris XII Val de Marne, 2008. http://tel.archives-ouvertes.fr/tel-00399469.

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Cette étude traite de l'identification de système dynamique non-linéaire. Une architecture multimodèle capable de surmonter certaines difficultés de l'architecture neuronale de type MLP a été étudiée. L'approche multimodèle consiste à représenter un système complexe par un ensemble de modèles de structures simples à validité limitée dans des zones bien définies. A la place de la structure affine des modèles locaux généralement utilisée, cette étude propose une structure polynômiale plus générale, capable de mieux appréhender les non-linéarités locales, réduisant ainsi le nombre de modèles loca

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Hsu, Shuo-Huan, and 許碩桓. "Fuzzy Model Identification." Thesis, 1998. http://ndltd.ncl.edu.tw/handle/94879299895065269443.

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碩士<br>國立臺灣大學<br>化學工程學系研究所<br>86<br>A simple method for generating a multiple-input/single-outputcrisp-type fuzzy model from observed data is presented in this article.The crisp-type fuzzy mod el is composed of triangular fuzzy partitionsfor inputs and singletons for the output. Three steps are proposedin this identification method: initializing phase, growing phase,and refining phase. For a set of observed input/output d ata pairs,the structure and the parameters of a suitable fuzzy model withrequi red

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Lin, Chih-Chien, and 林志謙. "Fuzzy C-Regression Model Based Fuzzy Model Identification and Controller Design." Thesis, 2001. http://ndltd.ncl.edu.tw/handle/01005916024628069803.

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碩士<br>大同大學<br>電機工程研究所<br>89<br>Fuzzy c-means (FCM) is usually used in partitioning data, but it is unreasonable applying FCM to partitioning the input-output space in that data in the space grouped nearby do not imply that they have functional relations. Fuzzy c-regression model (FCRM) clustering algorithm that uses functional relations instead of individual points as its cluster representatives provides a mathematical tool to partition the input-output space reasonably and efficiently. If we choose its cluster representatives as linear equations that fit the consequent parts of T-S fuzzy mo

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Chang, Wei-En, and 張維恩. "Fuzzy model identification by FCM clustering algorithm and fuzzy controller design." Thesis, 1999. http://ndltd.ncl.edu.tw/handle/37147018727277599666.

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碩士<br>大同工學院<br>電機工程研究所<br>87<br>ABSTRACT Fuzzy controllers have been successfully applied in many cases to which conventional control algorithms are difficult to be applied. Recently, it was proven that fuzzy systems are capable of approximating any real continuous function to arbitrary accuracy. This result motivates us to use the fuzzy systems as identifiers for nonlinear dynamic systems, and then design the fuzzy controllers based on the fuzzy system. In the process of the identification, most of the techniques used in the literatures for fuzzy c-mean (FCM) clusterin

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李輝煌. "Fuzzy model identification and controller design of nonlinear systems." Thesis, 1994. http://ndltd.ncl.edu.tw/handle/76246464257387152258.

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Shaw, Ian Stephan. "Expert fuzzy control based upon man-in-the-loop model identification." Thesis, 2014. http://hdl.handle.net/10210/11191.

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M.Ing. (Electrical & Electronic Engineering)<br>A dynamic process is considered modelled and identified when the model can predict its future behaviour as a result of a known stimulus. However, practical reality is complex and it is quite difficult to totally encompass a model representing a physical phenomenon in a mathematical formulation. Besides, to keep such formulations tractable, certain restrictive assumptions such as, for example, linearity, are often required. The common feature of general control-theoretic methods used for modelling is that they presuppose the valid and accurate kno

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Jen-Yen, Tsai, and 蔡仁彥. "Hyperspectral Data Identification Using Gaussian Model and Fuzzy-RCE Network." Thesis, 2000. http://ndltd.ncl.edu.tw/handle/21575114043979402160.

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碩士<br>國立臺灣大學<br>電機工程學研究所<br>88<br>Hyperspectral image data can provide sufficient spectral sampling to define unique spectral signatures on a per-pixel basis and give rise to the possibility of performing direct surface materials identification for geological studies. Gaussian model is commonly used to approximate the reflectance spectrum as a series of Gaussian curves with each curve characterized by the parameters as center position, width and strength. A spectral identifier using the Fuzzy-RCE neural network has been developed to identify the hyperspectral data on the basis of the Gaussian

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Chen, Wei-yin, and 陳維吟. "FUZZY BILINEAR MODEL IDENTIFICATION WITH CLUSTER VALIDITY CRITERIA AND ITS APPLICATIONS." Thesis, 2009. http://ndltd.ncl.edu.tw/handle/12135616464099452548.

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碩士<br>大同大學<br>電機工程學系(所)<br>97<br>In this thesis, our objective is to use T-S fuzzy bilinear model to describe nonlinear system with high accuracy and as fewer IF-THEN rules as possible via input and output data which collect from original nonlinear system. The modeling process will use fuzzy clustering algorithm for bilinear models, identification of bilinear models, cluster validity criteria for bilinear models, and fuzzy bilinear modeling algorithm. Hence, we will modify the FCRM clustering algorithm to suit to bilinear modes, choose an identification method for clustering algorithm, propose

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Liang, Han-Hsi, and 梁漢溪. "The Dynamic System Identification of Adaptive Fuzzy Model from Numerical Data." Thesis, 1997. http://ndltd.ncl.edu.tw/handle/65618903533406533826.

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博士<br>國立中央大學<br>土木工程學系<br>85<br>The algorithms of dynamic system identification and adaptive fuzzy model formulti-input/single-output systems are proposed to generate fuzzy rules andthen traslated is to a fuzzy relation using input-output data. Based on thePedrycz''s refenerce fuzzy sets, we present improved methods to identify fuzzyrelation and show that the proposed identification alogrithm can providea fuzzy model with a fairly high accuracy and that the proposed adaptivealogrith

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(20390), Baolin Wu. "Fuzzy modelling and identification with genetic algorithms based learning." Thesis, 1996. https://figshare.com/articles/thesis/Fuzzy_modelling_and_identification_with_genetic_algorithms_based_learning/21345057.

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<p>Modelling is an essential step towards a solution to complex system problems. Traditional mathematical methods are inadequate in describing the complex systems when the complexity increases. Fuzzy logic has provided an alternative way in dealing with complexity in real world.</p> <p>This thesis looks at a practical approach for complex system modelling using fuzzy logic. This approach is usually called fuzzy modelling. The main aim of this thesis is to explore the capabilities of fuzzy logic in complex system modelling using available data. The fuzzy model concerned is the Sugeno-Takage-Kan

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Huang, Yuan-Ruey, and 黃元瑞. "Identification of Servomechanism Model Based on a Chebyshev Recurrent Neuro-Fuzzy Network." Thesis, 2007. http://ndltd.ncl.edu.tw/handle/38762953636606724808.

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博士<br>中原大學<br>機械工程研究所<br>95<br>A novel nine-layer neuro-fuzzy model, Chebyshev recurrent neuro-fuzzy (CRNF) network, is developed based on the combination of the Takagi-Sugeno-Kang (TSK) fuzzy model and the six-layer Chebyshev recurrent neural network (CRNN) for the modeling of nonlinear dynamic systems. System nonlinearity is approximated by enhancing the input dimensions of the consequent parts in the fuzzy rules due to functional expansion of a Chebyshev polynomial. The modeling of a belt servomechanism and ball-screw-driven servomechanism, based on the CRNF network, is studied under the Ma

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Wu, Kun-Huang, and 吳坤皇. "Identification and Controller Design ofA Brushless DC Motor Based onTakagi—Sugeno Fuzzy Model." Thesis, 2004. http://ndltd.ncl.edu.tw/handle/64513029443793718033.

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碩士<br>中原大學<br>電機工程研究所<br>92<br>This thesis provides a T-S fuzzy model identification method for position control system of DC brushless rotary motor. Then according to the identified model, the fuzzy logic controller (FLC) is designed. Although the FLC design does not need to know the plant model, however, in simulation, a model is needed for its response. In identification, an adaptive genetic algorithm (AGA) is used for optimal searching of the scaling factors, the antecedent and consequent parameters of the T-S fuzzy model. The optimal one is to minimize the sum of square error (SSE) betw

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Su, Jui-Yiao, and 蘇瑞堯. "Fuzzy Model Identification by FCRM Clustering with Novel Cluster Validity Criteria and its Applications." Thesis, 2007. http://ndltd.ncl.edu.tw/handle/9ybeck.

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博士<br>大同大學<br>電機工程學系(所)<br>95<br>In this thesis, an effective approach is developed to establish fuzzy models for a given nonlinear system. Firstly, the fuzzy c-regression model (FCRM) clustering technique is applied to partition the product space of the given input-output data into hyper-plan-shaped clusters. Each cluster is essentially a basis of the fuzzy rule that describes the system behavior, and the number of clusters is just the number of fuzzy rules. Particularly, several novel cluster validity criteria for FCRM clustering are set up to choose the appropriate number of clusters (rules

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ZHONG, MING-JI, and 鐘明吉. "Successive identification of a fuzzy model and its application to a time-delay system." Thesis, 1992. http://ndltd.ncl.edu.tw/handle/23263061175606878763.

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Hou, Pei-Ling, and 侯佩伶. "Fuzzy Model Identification and Control System Design for Coagulation Chemical Dosing of Potable Water." Thesis, 2005. http://ndltd.ncl.edu.tw/handle/88493389866285571402.

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碩士<br>國立臺灣大學<br>化學工程學研究所<br>93<br>In Taiwan, which is known for numerous rivers and lakes, the raw water required for water purification plants comes mainly from the surface of rivers or creeks. The raw water is, therefore, significantly subject to the impact of a capricious climate. Especially during torrential storms or typhoons, sandy soil washed out by storms and muddy raw water brought by the floodwater released by reservoirs tremendously challenges the competence of water purification plants in the capacity to treat the water. The process used to remove pellet substances out of water n

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Lin, Chin Gao, and 林擎國. "Fuzzy Neural Network Approaches to Auditory Image Localization Control and Room Acoustic Model Identification." Thesis, 1993. http://ndltd.ncl.edu.tw/handle/52919850503743211596.

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碩士<br>國立交通大學<br>電信研究所<br>81<br>This thesis includes two parts. The first part describles the design of a novel-based acoustic control used for the equalization of the response of a sound reproduction system. Since, the traditional adaptive equalizer is capable of dealing with linear systems or specific nonlinear systems, the time- delay feedforward neural network (TDNN) which bave the capability to learn arbitrary nonlinearity and process the temporal audio patterns are particularly recogni

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"Fuzzy identification and manipulation of source channels in channel network derived from Digital Elevation Model." Thesis, 1996. http://hdl.handle.net/10388/etd-05242012-090836.

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The accuracy of channel networks extracted automatically from a grid digital elevation model (DEM) generally relies on the selection of a Critical Source Area (CSA) threshold. Using an unique CSA within an entire DEM will lead to the assumption that all source (1st order) channels have an equal contributing area. Thus, overshoot and undershoot problems, excessive and deficient representation of source channels, appear frequently in the channel network, especially for a DEM of a hydrologically heterogeneous region. This research focused on these problems by introducing fuzzy set theory for sour

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Quiroga, Jabid Eduardo Mendez. "Stator winding fault detection for a PMSM using fuzzy logic classifier and neural network model identification." 2008. http://etd.lib.fsu.edu/theses/available/etd-04282008-100002.

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Thesis (M.S.)--Florida State University, 2008<br>Advisor: Dave A. Cartes, Florida State University, College of Engineering, Dept. of Mechanical Engineering. Title and description from dissertation home page (viewed June 11, 2008). Document formatted into pages; contains xii, 82 pages. Includes bibliographical references.

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Lai, Xin-Hua, and 賴信樺. "Identification of Takagi-Sugeno Fuzzy-Model-Based Dynamic Systems using Orthogonal-Functions Approach and Genetic Algorithm." Thesis, 2010. http://ndltd.ncl.edu.tw/handle/06952676798379931982.

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碩士<br>國立高雄第一科技大學<br>系統資訊與控制研究所<br>98<br>The main purpose of this thesis is to propose an integrative method which integrates the orthogonal-function approach (OFA) and the hybrid Taguchi-genetic algorithm (HTGA) for solving the identification problem of Takagi-Sugeno (TS) fuzzy-model-based dynamic system. First, the OFA can solve the solution for the TS fuzzy-model-based dynamic equation. Then, the HTGA can search the optimal antecedent and consequent solutions simultaneously for the identification problem of TS fuzzy-model-based dynamic system. Finally, the proposed approach is effectively ap

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Biswal, Suryakanta. "Uncertainty Based Damage Identification and Prediction of Long-Time Deformation in Concrete Structures." Thesis, 2016. http://etd.iisc.ac.in/handle/2005/3143.

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Uncertainties are present in the inverse analysis of damage identification with respect to the given measurements, mainly the modelling uncertainties and the measurement uncertainties. Modelling uncertainties occur due to constructing a representative model of the real structure through finite element modelling, and representing damage in the real structures through changes in material parameters of the finite element model (assuming smeared crack approach). Measurement uncertainties are always present in the measurements despite the accuracy with which the measurements are measured or the pre

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Biswal, Suryakanta. "Uncertainty Based Damage Identification and Prediction of Long-Time Deformation in Concrete Structures." Thesis, 2016. http://hdl.handle.net/2005/3143.

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Uncertainties are present in the inverse analysis of damage identification with respect to the given measurements, mainly the modelling uncertainties and the measurement uncertainties. Modelling uncertainties occur due to constructing a representative model of the real structure through finite element modelling, and representing damage in the real structures through changes in material parameters of the finite element model (assuming smeared crack approach). Measurement uncertainties are always present in the measurements despite the accuracy with which the measurements are measured or the pre

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Chen, Yi-Ru, and 陳怡儒. "A Systematic Approach in the Identification of Fuzzy Models." Thesis, 1997. http://ndltd.ncl.edu.tw/handle/58153930758375628240.

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碩士<br>大同工學院<br>資訊工程學系<br>85<br>The purpose of this thesis is to propose a systematic and effective method toconstruct different types of fuzzy models such as Tsukamoto-type, Mamdani-type,and Takagi-Sugeno-Kang-type fuzzy models. The main processes of the proposedsystematic fuzzy modeling scheme are as follows. The first step is to fuzzycluster the given data and then to find the cluster centers. However, thetraditional clustering methods such as fuzzy c-means algorithm and mountainclusterin

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"Fuzzy rule base identification via singular value decomposition." 1999. http://library.cuhk.edu.hk/record=b6073219.

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by Stephen Chi-tin Yang.<br>"Sept. 28, 1999."<br>Thesis (Ph.D.)--Chinese University of Hong Kong, 1999.<br>Includes bibliographical references (p. 158-163).<br>Electronic reproduction. Hong Kong : Chinese University of Hong Kong, [2012] System requirements: Adobe Acrobat Reader. Available via World Wide Web.<br>Electronic reproduction. Ann Arbor, MI : ProQuest Information and Learning Company, [200-] System requirements: Adobe Acrobat Reader. Available via World Wide Web.<br>Mode of access: World Wide Web.<br>Abstracts in English and Chinese.

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Tewari, Ashutosh Urquidi-MacDonald Mirna. "Prior knowledge based identification of Takagi-Sugeno- Kang fuzzy models for static nonlinear systems." 2009. http://etda.libraries.psu.edu/theses/approved/WorldWideIndex/ETD-3522/index.html.

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Renners, Ingo [Verfasser]. "Data-driven system identification via evolutionary retrieval of Takagi-Sugeno fuzzy models / von: Ingo Renners." 2004. http://d-nb.info/974452351/34.

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Bruder, Slawa Romana. "Prediction of Spatial-Temporal Distribution of Algal Metabolites in Eagle Creek Reservoir, Indianapolis, IN." Thesis, 2012. http://hdl.handle.net/1805/3043.

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Abstract:

Indiana University-Purdue University Indianapolis (IUPUI)<br>In this research, Environmental Fluid Dynamic Code (EFDC) and Adaptive- Networkbased Fuzzy Inference System Models (ANFIS) were developed and implemented to determine the spatial-temporal distribution of cyanobacterial metabolites: 2-MIB and geosmin, in Eagle Creek Reservoir, IN. The research is based on the current need for understanding algae dynamics and developing prediction methods for algal taste and odor release events. In this research the methodology for prediction of 2-MIB and geosmin production was explored. The app

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