Recurrent Interval Type 2 Fuzzy Neural Network Using Asymmetric Membership Functions

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Recurrent Interval Type-2 Fuzzy Neural Network Using Asymmetric Membership Functions

Author : Ching-Hung Lee
Publisher :
ISBN 13 : 9789537619084
Total Pages : pages
Book Rating : 4.6/5 (19 download)

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Book Synopsis Recurrent Interval Type-2 Fuzzy Neural Network Using Asymmetric Membership Functions by : Ching-Hung Lee

Download or read book Recurrent Interval Type-2 Fuzzy Neural Network Using Asymmetric Membership Functions written by Ching-Hung Lee and published by . This book was released on 2008 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: This article has introduced a novel recurrent interval type-2 fuzzy neural network with asymmetric membership functions, which utilizes Lyapunov stability theorem to prove the stability of the system. The novel RiT2FNN-A use the interval asymmetric type-2 fuzzy sets implements the FLS in a five-layer neural network structure which contains four layer forward network and a feedback layer. According to the Lyapunov theorem and gradient descent method, the convergence of RiT2FNN-A is guaranteed and the corresponding learning algorithm is derived. Moreover, the RIT2FNN-A capability to temporarily store information allowed us to extend the application domain to include temporal problem. In application, We have found that the proposed RiT2FNN-A can use a smaller network structure and a small number of tuning parameters than the feed-forward fuzzy neural networks to obtain similar or better performance. It can successfully also approximate to a dynamic system mapping as accurately as desired.

Type-2 Fuzzy Neural Networks and Their Applications

Author : Rafik Aziz Aliev
Publisher : Springer
ISBN 13 : 3319090720
Total Pages : 203 pages
Book Rating : 4.3/5 (19 download)

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Book Synopsis Type-2 Fuzzy Neural Networks and Their Applications by : Rafik Aziz Aliev

Download or read book Type-2 Fuzzy Neural Networks and Their Applications written by Rafik Aziz Aliev and published by Springer. This book was released on 2014-09-08 with total page 203 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book deals with the theory, design principles, and application of hybrid intelligent systems using type-2 fuzzy sets in combination with other paradigms of Soft Computing technology such as Neuro-Computing and Evolutionary Computing. It provides a self-contained exposition of the foundation of type-2 fuzzy neural networks and presents a vast compendium of its applications to control, forecasting, decision making, system identification and other real problems. Type-2 Fuzzy Neural Networks and Their Applications is helpful for teachers and students of universities and colleges, for scientists and practitioners from various fields such as control, decision analysis, pattern recognition and similar fields.

Issues in Artificial Intelligence, Robotics and Machine Learning: 2013 Edition

Author :
Publisher : ScholarlyEditions
ISBN 13 : 1490111212
Total Pages : 1887 pages
Book Rating : 4.4/5 (91 download)

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Book Synopsis Issues in Artificial Intelligence, Robotics and Machine Learning: 2013 Edition by :

Download or read book Issues in Artificial Intelligence, Robotics and Machine Learning: 2013 Edition written by and published by ScholarlyEditions. This book was released on 2013-05-01 with total page 1887 pages. Available in PDF, EPUB and Kindle. Book excerpt: Issues in Artificial Intelligence, Robotics and Machine Learning: 2013 Edition is a ScholarlyEditions™ book that delivers timely, authoritative, and comprehensive information about Expert Systems. The editors have built Issues in Artificial Intelligence, Robotics and Machine Learning: 2013 Edition on the vast information databases of ScholarlyNews.™ You can expect the information about Expert Systems in this book to be deeper than what you can access anywhere else, as well as consistently reliable, authoritative, informed, and relevant. The content of Issues in Artificial Intelligence, Robotics and Machine Learning: 2013 Edition has been produced by the world’s leading scientists, engineers, analysts, research institutions, and companies. All of the content is from peer-reviewed sources, and all of it is written, assembled, and edited by the editors at ScholarlyEditions™ and available exclusively from us. You now have a source you can cite with authority, confidence, and credibility. More information is available at http://www.ScholarlyEditions.com/.

A Recurrent Self-Evolving Interval Type-2 Fuzzy Neural Network for Dynamic System Processing and Its FPGA Implementation

Author :
Publisher :
ISBN 13 :
Total Pages : 0 pages
Book Rating : 4.:/5 (142 download)

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Book Synopsis A Recurrent Self-Evolving Interval Type-2 Fuzzy Neural Network for Dynamic System Processing and Its FPGA Implementation by :

Download or read book A Recurrent Self-Evolving Interval Type-2 Fuzzy Neural Network for Dynamic System Processing and Its FPGA Implementation written by and published by . This book was released on 2008 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Dynamical Near Optimal Training for Interval Type-2 Fuzzy Neural Network (T2FNN) with Genetic Algorithm

Author : Martin Chun-Sheng Cheng
Publisher :
ISBN 13 :
Total Pages : pages
Book Rating : 4.:/5 (223 download)

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Book Synopsis Dynamical Near Optimal Training for Interval Type-2 Fuzzy Neural Network (T2FNN) with Genetic Algorithm by : Martin Chun-Sheng Cheng

Download or read book Dynamical Near Optimal Training for Interval Type-2 Fuzzy Neural Network (T2FNN) with Genetic Algorithm written by Martin Chun-Sheng Cheng and published by . This book was released on 2003 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Abstract: Type-2 fuzzy logic system (FLS) cascaded with neural network, called type-2 fuzzy neural network (T2FNN), is presented in this paper to handle uncertainty with dynamical optimal learning. A T2FNN consists of type-2 fuzzy linguistic process as the antecedent part and the two-layer interval neural network as the consequent part. A general T2FNN is computational intensive due to the complexity of type 2 to type 1 reduction. Therefore the interval T2FNN is adopted in this paper to simplify the computational process. The dynamical optimal training algorithm for the two-layer consequent part of interval T2FNN is first developed. The stable and optimal left and right learning rates for the interval neural network, in the sense of maximum error reduction, can be derived for each iteration in the training process (back propagation). It can also be shown both learning rates can not be both negative. Further, due to variation of the initial MF parameters, i.e. the spread level of uncertain means or deviations of interval Gaussian MFs, the performance of back propagation training process may be affected. To achieve better total performance, a genetic algorithm (GA) is designed to search better-fit spread rate for uncertain means and near optimal learnings for the antecedent part. Several examples are fully illustrated. Excellent results are obtained for the truck backing-up control and the identification of nonlinear system, which yield more improved performance than those using type-1 FNN.

A Self-Evolving Interval Type-2 Fuzzy Neural Network and Its Hardware Implementation

Author :
Publisher :
ISBN 13 :
Total Pages : 0 pages
Book Rating : 4.:/5 (137 download)

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Book Synopsis A Self-Evolving Interval Type-2 Fuzzy Neural Network and Its Hardware Implementation by :

Download or read book A Self-Evolving Interval Type-2 Fuzzy Neural Network and Its Hardware Implementation written by and published by . This book was released on 2007 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Soft Computing for Data Analytics, Classification Model, and Control

Author : Deepak Gupta
Publisher : Springer Nature
ISBN 13 : 3030920267
Total Pages : 165 pages
Book Rating : 4.0/5 (39 download)

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Book Synopsis Soft Computing for Data Analytics, Classification Model, and Control by : Deepak Gupta

Download or read book Soft Computing for Data Analytics, Classification Model, and Control written by Deepak Gupta and published by Springer Nature. This book was released on 2022-01-30 with total page 165 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents a set of soft computing approaches and their application in data analytics, classification model, and control. The basics of fuzzy logic implementation for advanced hybrid fuzzy driven optimization methods has been covered in the book. The various soft computing techniques, including Fuzzy Logic, Rough Sets, Neutrosophic Sets, Type-2 Fuzzy logic, Neural Networks, Generative Adversarial Networks, and Evolutionary Computation have been discussed and they are used on variety of applications including data analytics, classification model, and control. The book is divided into two thematic parts. The first thematic section covers the various soft computing approaches for text classification and data analysis, while the second section focuses on the fuzzy driven optimization methods for the control systems. The chapters has been written and edited by active researchers, which cover hypotheses and practical considerations; provide insights into the design of hybrid algorithms for applications in data analytics, classification model, and engineering control.

Nonlinear System Identification

Author : Oliver Nelles
Publisher : Springer Science & Business Media
ISBN 13 : 3662043238
Total Pages : 785 pages
Book Rating : 4.6/5 (62 download)

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Book Synopsis Nonlinear System Identification by : Oliver Nelles

Download or read book Nonlinear System Identification written by Oliver Nelles and published by Springer Science & Business Media. This book was released on 2013-03-09 with total page 785 pages. Available in PDF, EPUB and Kindle. Book excerpt: Written from an engineering point of view, this book covers the most common and important approaches for the identification of nonlinear static and dynamic systems. The book also provides the reader with the necessary background on optimization techniques, making it fully self-contained. The new edition includes exercises.

Fusion of Neural Networks, Fuzzy Systems and Genetic Algorithms

Author : Lakhmi C. Jain
Publisher : CRC Press
ISBN 13 : 1000715124
Total Pages : 363 pages
Book Rating : 4.0/5 (7 download)

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Book Synopsis Fusion of Neural Networks, Fuzzy Systems and Genetic Algorithms by : Lakhmi C. Jain

Download or read book Fusion of Neural Networks, Fuzzy Systems and Genetic Algorithms written by Lakhmi C. Jain and published by CRC Press. This book was released on 2020-01-29 with total page 363 pages. Available in PDF, EPUB and Kindle. Book excerpt: Artificial neural networks can mimic the biological information-processing mechanism in - a very limited sense. Fuzzy logic provides a basis for representing uncertain and imprecise knowledge and forms a basis for human reasoning. Neural networks display genuine promise in solving problems, but a definitive theoretical basis does not yet exist for their design. Fusion of Neural Networks, Fuzzy Systems and Genetic Algorithms integrates neural net, fuzzy system, and evolutionary computing in system design that enables its readers to handle complexity - offsetting the demerits of one paradigm by the merits of another. This book presents specific projects where fusion techniques have been applied. The chapters start with the design of a new fuzzy-neural controller. Remaining chapters discuss the application of expert systems, neural networks, fuzzy control, and evolutionary computing techniques in modern engineering systems. These specific applications include: direct frequency converters electro-hydraulic systems motor control toaster control speech recognition vehicle routing fault diagnosis Asynchronous Transfer Mode (ATM) communications networks telephones for hard-of-hearing people control of gas turbine aero-engines telecommunications systems design Fusion of Neural Networks, Fuzzy Systems and Genetic Algorithms covers the spectrum of applications - comprehensively demonstrating the advantages of fusion techniques in industrial applications.

Computational Intelligence Paradigms

Author : L. C. Jain
Publisher : Springer Science & Business Media
ISBN 13 : 3540794735
Total Pages : 281 pages
Book Rating : 4.5/5 (47 download)

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Book Synopsis Computational Intelligence Paradigms by : L. C. Jain

Download or read book Computational Intelligence Paradigms written by L. C. Jain and published by Springer Science & Business Media. This book was released on 2008-06-12 with total page 281 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book features research on the innovative applications of advanced computational intelligence paradigms. Coverage includes architectures of computational intelligence paradigms, knowledge discovery, pattern classification, and gene linkage analysis.

Elementary Fuzzy Matrix Theory and Fuzzy Models for Social Scientists

Author : W. B. Vasantha Kandasamy, Florentin Smarandache, K. Ilanthenral
Publisher : Infinite Study
ISBN 13 : 1599730057
Total Pages : 352 pages
Book Rating : 4.5/5 (997 download)

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Book Synopsis Elementary Fuzzy Matrix Theory and Fuzzy Models for Social Scientists by : W. B. Vasantha Kandasamy, Florentin Smarandache, K. Ilanthenral

Download or read book Elementary Fuzzy Matrix Theory and Fuzzy Models for Social Scientists written by W. B. Vasantha Kandasamy, Florentin Smarandache, K. Ilanthenral and published by Infinite Study. This book was released on 2007-03-01 with total page 352 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Soft Computing for Recognition Based on Biometrics

Author : Patricia Melin
Publisher : Springer Science & Business Media
ISBN 13 : 3642151108
Total Pages : 449 pages
Book Rating : 4.6/5 (421 download)

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Book Synopsis Soft Computing for Recognition Based on Biometrics by : Patricia Melin

Download or read book Soft Computing for Recognition Based on Biometrics written by Patricia Melin and published by Springer Science & Business Media. This book was released on 2010-09-20 with total page 449 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book describes bio-inspired models and applications of hybrid intelligent systems using soft computing techniques for image analysis and pattern recognition based on biometrics and other sources. Each section groups papers on a similar subject.

Neural Fuzzy Control Systems With Structure And Parameter Learning

Author : Chin-teng Lin
Publisher : World Scientific Publishing Company
ISBN 13 : 9813104708
Total Pages : 152 pages
Book Rating : 4.8/5 (131 download)

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Book Synopsis Neural Fuzzy Control Systems With Structure And Parameter Learning by : Chin-teng Lin

Download or read book Neural Fuzzy Control Systems With Structure And Parameter Learning written by Chin-teng Lin and published by World Scientific Publishing Company. This book was released on 1994-02-08 with total page 152 pages. Available in PDF, EPUB and Kindle. Book excerpt: A general neural-network-based connectionist model, called Fuzzy Neural Network (FNN), is proposed in this book for the realization of a fuzzy logic control and decision system. The FNN is a feedforward multi-layered network which integrates the basic elements and functions of a traditional fuzzy logic controller into a connectionist structure which has distributed learning abilities.In order to set up this proposed FNN, the author recommends two complementary structure/parameter learning algorithms: a two-phase hybrid learning algorithm and an on-line supervised structure/parameter learning algorithm.Both of these learning algorithms require exact supervised training data for learning. In some real-time applications, exact training data may be expensive or even impossible to get. To solve this reinforcement learning problem for real-world applications, a Reinforcement Fuzzy Neural Network (RFNN) is further proposed. Computer simulation examples are presented to illustrate the performance and applicability of the proposed FNN, RFNN and their associated learning algorithms for various applications.

Neural Networks and Statistical Learning

Author : Ke-Lin Du
Publisher : Springer Science & Business Media
ISBN 13 : 1447155718
Total Pages : 834 pages
Book Rating : 4.4/5 (471 download)

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Book Synopsis Neural Networks and Statistical Learning by : Ke-Lin Du

Download or read book Neural Networks and Statistical Learning written by Ke-Lin Du and published by Springer Science & Business Media. This book was released on 2013-12-09 with total page 834 pages. Available in PDF, EPUB and Kindle. Book excerpt: Providing a broad but in-depth introduction to neural network and machine learning in a statistical framework, this book provides a single, comprehensive resource for study and further research. All the major popular neural network models and statistical learning approaches are covered with examples and exercises in every chapter to develop a practical working understanding of the content. Each of the twenty-five chapters includes state-of-the-art descriptions and important research results on the respective topics. The broad coverage includes the multilayer perceptron, the Hopfield network, associative memory models, clustering models and algorithms, the radial basis function network, recurrent neural networks, principal component analysis, nonnegative matrix factorization, independent component analysis, discriminant analysis, support vector machines, kernel methods, reinforcement learning, probabilistic and Bayesian networks, data fusion and ensemble learning, fuzzy sets and logic, neurofuzzy models, hardware implementations, and some machine learning topics. Applications to biometric/bioinformatics and data mining are also included. Focusing on the prominent accomplishments and their practical aspects, academic and technical staff, graduate students and researchers will find that this provides a solid foundation and encompassing reference for the fields of neural networks, pattern recognition, signal processing, machine learning, computational intelligence, and data mining.

Off-road Vehicle Dynamics

Author : Hamid Taghavifar
Publisher : Springer
ISBN 13 : 331942520X
Total Pages : 191 pages
Book Rating : 4.3/5 (194 download)

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Book Synopsis Off-road Vehicle Dynamics by : Hamid Taghavifar

Download or read book Off-road Vehicle Dynamics written by Hamid Taghavifar and published by Springer. This book was released on 2016-07-27 with total page 191 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book deals with the analysis of off-road vehicle dynamics from kinetics and kinematics perspectives and the performance of vehicle traversing over rough and irregular terrain. The authors consider the wheel performance, soil-tire interactions and their interface, tractive performance of the vehicle, ride comfort, stability over maneuvering, transient and steady state conditions of the vehicle traversing, modeling the aforementioned aspects and optimization from energetic and vehicle mobility perspectives. This book brings novel figures for the transient dynamics and original wheel terrain dynamics at on-the-go condition.

Intelligent Control Systems Using Computational Intelligence Techniques

Author : A.E. Ruano
Publisher : IET
ISBN 13 : 0863414893
Total Pages : 478 pages
Book Rating : 4.8/5 (634 download)

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Book Synopsis Intelligent Control Systems Using Computational Intelligence Techniques by : A.E. Ruano

Download or read book Intelligent Control Systems Using Computational Intelligence Techniques written by A.E. Ruano and published by IET. This book was released on 2005-07-18 with total page 478 pages. Available in PDF, EPUB and Kindle. Book excerpt: Intelligent Control techniques are becoming important tools in both academia and industry. Methodologies developed in the field of soft-computing, such as neural networks, fuzzy systems and evolutionary computation, can lead to accommodation of more complex processes, improved performance and considerable time savings and cost reductions. Intelligent Control Systems using Computational Intellingence Techniques details the application of these tools to the field of control systems. Each chapter gives and overview of current approaches in the topic covered, with a set of the most important references in the field, and then details the author's approach, examining both the theory and practical applications.

Introduction to Genetic Algorithms

Author : S.N. Sivanandam
Publisher : Springer Science & Business Media
ISBN 13 : 3540731903
Total Pages : 453 pages
Book Rating : 4.5/5 (47 download)

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Book Synopsis Introduction to Genetic Algorithms by : S.N. Sivanandam

Download or read book Introduction to Genetic Algorithms written by S.N. Sivanandam and published by Springer Science & Business Media. This book was released on 2007-10-24 with total page 453 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book offers a basic introduction to genetic algorithms. It provides a detailed explanation of genetic algorithm concepts and examines numerous genetic algorithm optimization problems. In addition, the book presents implementation of optimization problems using C and C++ as well as simulated solutions for genetic algorithm problems using MATLAB 7.0. It also includes application case studies on genetic algorithms in emerging fields.