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Computational Intelligence

the aspects of fuzzy, neural and evolutionary approaches with worked out examples, MATLAB(R) exercises and applications in each chapter;

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Fuzzy and Neural Approaches in Engineering

Neural networks and fuzzy systems represent two distinct technologies that deal with uncertainty. This definitive book presents the;

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Fuzzy Neural Intelligent Systems

Although fuzzy systems and neural networks are central to the field of soft computing, most research work has focused on the development;

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Modeling and Control of Uncertain Nonlinear Systems with Fuzzy Equations and Z-Number

equations There are various numerical and analytical approaches to the modeling and control of uncertain nonlinear systems. Fuzzy logic theory;

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Artificial Intelligence and Expert Systems

engineering, expert systems, neural networks, and fuzzy logic, etc. The book has been structured into five parts with an emphasis on expert systems;

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Fusion of Neural Networks, Fuzzy Systems and Genetic Algorithms

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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Fundamentals of Computational Intelligence

covers the three fundamental topics that form the basis of computational intelligence: neural networks, fuzzy systems, and evolutionary;

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Advanced Fuzzy Logic Approaches in Engineering Science

apprehension in modern years due to high-tech industrial processes with ever-increasing levels of complexity. Advanced Fuzzy Logic Approaches;

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Diffuse Algorithms for Neural and Neuro-Fuzzy Networks

approaches to training neural and neuro-fuzzy networks. This book is divided into six chapters. Chapter 1 consists of plants models reviews, problems;

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Engineering Applications of Neural Networks

machine, machine learning applications, predictive models, fuzzy and recommender systems, recurrent neural networks, spiking neural networks.;

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A First Course in Fuzzy and Neural Control

given situation. A First Course in Fuzzy and Neural Control is designed to build the foundation needed to make those decisions. It begins;

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Neuro-fuzzy Control of Industrial Systems with Actuator Nonlinearities

Neural networks and fuzzy systems are model free control design approaches that represent an advantage over classical control when dealing;

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Neural Networks & Fuzzy-Logic Control On Personal Computers & Workstations + D3

algorithms with pulldown menus. This hands-on tutorial demonstrates both neural networks and fuzzy-logic control with a different approach. A natural;

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Learning from Data

An interdisciplinary framework for learning methodologies-covering statistics, neural networks, and fuzzy logic, this book provides a;

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Computational Intelligence Paradigms

neural networks, fuzzy systems, evolutionary computation, genetic algorithms and programming, and swarm intelligence. It covers numerous;

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Computational Intelligence Paradigms

neural networks, fuzzy systems, evolutionary computation, genetic algorithms and programming, and swarm intelligence. It covers numerous;

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Deep Neuro-Fuzzy Systems with Python

Gain insight into fuzzy logic and neural networks, and how the integration between the two models makes intelligent systems in the current;

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Fuzzy Logic and Neural Networks

In this title, fuzzy logic and neural networks have been discussed in detail through illustrative examples, methods and generic;

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Fuzzy Control and Identification

This book gives an introduction to basic fuzzy logic and Mamdani and Takagi-Sugeno fuzzy systems. The text shows how these can be used to;

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Swarm, Evolutionary, and Memetic Computing and Fuzzy and Neural Computing

Memetic Computing, SEMCCO 2019, and 5th International Conference on Fuzzy and Neural Computing, FANCCO 2019, held in Maribor, Slovenia, in July;

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Recent Advances in Intelligent Engineering

This book gathers contributions on fuzzy neural control, intelligent and non-linear control, dynamic systems and cyber-physical systems. It;

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Engineering Applications of Neural Networks

; intelligent telecommunications modeling; fuzzy modeling; robotics and control; smart cameras; pattern recognition-facial mapping; classification;

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Neural Networks And Artificial Intelligence For Biomedical Engineering

biomedicine based on current theory and applications of neural networks, artificial intelligence, and other methods for the development of decision;

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Application of Artificial Intelligence in Process Control

, neural network, and object oriented-based approaches in AI. Part two covers the application to control engineering, part three: Real-Time Issues;

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Knowledge-Based Neurocomputing

integrates the merits of symbolic fuzzy rule-bases and sub-symbolic artificial neural networks, and yields a new approach for knowledge-based;

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Nonlinear Biomedical Signal Processing, Volume 1

newest theories and applications of fuzzy logic, neural networks, and algorithms in biomedicine. Nonlinear Biomedical Signal Processing, Volume I;

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Fundamentals of Soft Computing and Intelligent System

artificial intelligence, and comprises fuzzy logic, neural networks and probabilistic reasoning techniques. It tries to imitate human reasoning in a;

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