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Neural networks and fuzzy systems are model free control design approaches that represent an advantage over classical control when dealing;
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, system identification and other real problems. Type-2 Fuzzy Neural Networks and Their Applications is helpful for teachers and students;
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the development of a suitable framework for fuzzy logic, neural networks and evolutionary computing, neuro-fuzzy systems, evolutionary-fuzzy;
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in solving problems, but a definitive theoretical basis does not yet exist for their design. Fusion of Neural Networks, Fuzzy Systems and Genetic;
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AN INDISPENSABLE RESOURCE FOR ALL THOSE WHO DESIGN AND IMPLEMENT TYPE-1 AND TYPE-2 FUZZY NEURAL NETWORKS IN REAL TIME SYSTEMS
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This book describes the latest advances in fuzzy logic, neural networks and optimization algorithms, as well as their hybrid combinations;
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This book describes the latest advances in fuzzy logic, neural networks and optimization algorithms, as well as their hybrid combinations;
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of the theories, algorithms, and designs of systems for specific applications. There has been little theoretical support for fuzzy neural systems;
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This book comprises papers on diverse aspects of fuzzy logic, neural networks, and nature-inspired optimization meta-heuristics and their;
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neural networks, this innovative volume provides a framework for control and modeling of uncertain nonlinear systems with applications to;
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on the screen; real simulation experiments then execute immediately.Neural Networks and Fuzzy-Logic Control introduces a;
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A general neural-network-based connectionist model, called Fuzzy Neural Network (FNN), is proposed in this book for the realization of a;
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Neural Networks Modelling and Control: Applications for Unknown Nonlinear Delayed Systems in Discrete Time focuses on modeling and;
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We describe in this book, recent developments on fuzzy logic, neural networks and optimization algorithms, as well as their hybrid;
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application of intelligent control, particularly employing fuzzy logic, neural networks, and evolutionary computing.;
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book focuses on the use of fuzzy logic and neural networks to control power grids and adapt them to changing requirements. Chapters cover fuzzy;
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Diffuse Algorithms for Neural and Neuro-Fuzzy Networks: With Applications in Control Engineering and Signal Processing presents new;
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This book describes recent advances on fuzzy logic, neural networks and optimization algorithms, as well as their hybrid combinations, and;
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applications. Extensive and carefully selected references is an invaluable resource for further study of fuzzy logic and neural networks. Each chapter;
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real-time control, military, and operating system applications. A set of fuzzy rules were also developed to model the dynamics of the software;
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language, heart disease diagnosis utilizing hybrid fuzzy wavelet neural network, and hybrid neural network architecture for online learning;
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multiversion neural computing. The book concludes by examining various neural network applications, such as neuron-fuzzy control systems and image;
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neural networks, fuzzy systems, evolutionary computation, genetic algorithms and programming, and swarm intelligence. It covers numerous;
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neural networks, fuzzy systems, evolutionary computation, genetic algorithms and programming, and swarm intelligence. It covers numerous;
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considers current applications of fuzzy control systems. This book should be required reading for researchers, practitioners, and students;
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This book describes the latest advances in fuzzy logic, neural networks, and optimization algorithms, as well as their hybrid intelligent;
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presented in this book provide excellent tools for progressive learning. UNDERSTANDING NEURAL NETWORKS AND FUZZY LOGIC offers a simple presentation;
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