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Neural Fuzzy Control Systems With Structure And Parameter Learning

fuzzy logic control and decision system. The FNN is a feedforward multi-layered network which integrates the basic elements and functions of a;

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Fuzzy Neural Networks for Real Time Control Applications

> Delve into the type-2 fuzzy logic systems and become engrossed in the parameter update algorithms for type-1 and type-2 fuzzy neural networks;

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Neuro-fuzzy Control of Industrial Systems with Actuator Nonlinearities

with complicated nonlinear actuator dynamics. This book brings neural networks and fuzzy logic together with dynamical control systems. Each;

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

Systems with Fuzzy Equations and Z-Number presents a structured approach to the control and modeling of uncertain nonlinear systems in industry;

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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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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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Flight Mechanics Modeling and Analysis

fuzzy logic-based aspects in modeling and analysis of flight mechanics systems: aircraft parameter estimation, and reconfiguration of control;

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Fuzzy Control Systems

theory of fuzzy control systems. The second part deals with a variety of methodologies and algorithms used in the analysis and design of fuzzy;

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Fuzzy Intelligent Systems - Methodologies, Techniques, and Applications

current and future, need systematic training in the analytic theory and rigorous design of fuzzy control systems to keep up with and advance the;

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Parameter Identification for Induction Motor Drives

plant robust against parameter variations and disturbances. The soft computational methods such as Artificial Neural Networks and Fuzzy logic;

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Fuzzy Neural Intelligent Systems

networks, offers a better way of combining fuzzy logic systems with neural networks, and explores some of their engineering applications. Dividing;

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Fuzzy Set Theory and Advanced Mathematical Applications

coverage of the mathematical foundations of the theory, decision making and systems science, and recent developments in fuzzy neural control. The;

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Deep Neuro-Fuzzy Systems with Python

different types of deep neuro fuzzy classifiers, fuzzy neurons, and the adaptive learning capability of the neural networks. The book concludes by;

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Soft Computing with NeuroFuzzy Systems

-fuzzy systems, neuro-fuzzy inference systems, and neuro-fuzzy control. Section 1 focuses on intelligent neuro-fuzzy models, describing fuzzy;

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Fuzzy Logic Augmentation of Neural and Optimization Algorithms Theoretical Aspe

This book comprises papers on diverse aspects of fuzzy logic, neural networks, and nature-inspired optimization meta-heuristics and their;

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Artificial Intelligence for Smarter Power Systems

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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Congress on Intelligent Systems

, intelligent control systems, human motor control, game playing, evolutionary algorithms, swarm optimization, neural network, deep learning, supervised;

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Congress on Intelligent Systems

, intelligent control systems, human motor control, game playing, evolutionary algorithms, swarm optimization, neural network, deep learning, supervised;

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Type 2 Fuzzy Neural Networks and Their Applications

of the foundation of type-2 fuzzy neural networks and presents a vast compendium of its applications to control, forecasting, decision making;

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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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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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Recent Advances in Intelligent Control Systems

according to the style of control employed: fuzzy control; neural control; fuzzy neural control; and intelligent control. The contributions;

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Intelligent Control Systems With Labview(Tm)

tools of intelligent control: fuzzy logic systems; artificial neural networks; neuro-fuzzy systems; evolutionary methods; and predictive methods;

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Systems and Control

of dynamics and control. In particular, it presents neural networks, fuzzy systems, and genetic algorithms, and provides a concise introducton to;

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Hybrid Intelligent Systems in Control, Pattern Recognition and Medicine

This book describes the latest advances in fuzzy logic, neural networks and optimization algorithms, as well as their hybrid combinations;

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Hybrid Intelligent Systems in Control, Pattern Recognition and Medicine

This book describes the latest advances in fuzzy logic, neural networks and optimization algorithms, as well as their hybrid combinations;

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Differential Evolution Algorithm with Type-2 Fuzzy Logic for Dynamic Parameter Adaptation with Application to Intelligent Control

considering the fuzzy control area. The main idea is that these two areas together can help solve various control problems and to find better results;

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