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

Generalized Type-2 fuzzy systems. When we use fuzzy systems combined with the differential evolution algorithm, we can notice that the results;

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Fuzzy Logic Augmentation of Neural and Optimization Algorithms Theoretical Aspe

concepts and algorithms based on type-2 fuzzy logic for dynamic parameter adaptation in meta-heuristics. The second part discusses network theory;

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New Backpropagation Algorithm with Type-2 Fuzzy Weights for Neural Networks

methods was to find the optimal type-2 fuzzy inference systems for the neural network with type-2 fuzzy weights that permit to obtain the lowest;

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Fuzzy Logic Hybrid Extensions of Neural and Optimization Algorithms

algorithms based on type-1 and type-2 fuzzy logic and their applications. There also some papers that presents theory and practice of meta-heuristics;

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Recent Advances of Hybrid Intelligent Systems Based on Soft Computing

some papers with the main theme of type-1 and type-2 fuzzy logic, which basically consists of papers that propose new concepts and algorithms;

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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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Optimization of Type 2 Fuzzy Controllers Using the Bee Colony Algorithm

trajectory in an autonomous mobile robot. When Interval Type-2 Fuzzy Logic System is implemented to model the behavior of systems, the results show a;

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Hybrid Intelligent Systems in Control, Pattern Recognition and Medicine

type-2 fuzzy logic and their applications; the second explores new concepts and algorithms in neural networks and fuzzy logic applied to;

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Hybrid Intelligent Systems in Control, Pattern Recognition and Medicine

type-2 fuzzy logic and their applications; the second explores new concepts and algorithms in neural networks and fuzzy logic applied to;

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A New Bio-inspired Optimization Algorithm Based on the Self-defense Mechanism of Plants in Nature

is used for dynamic parameter adaptation in the algorithm.;

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Tracking Performance Of Maglev System Using Type-2 Fuzzy Logic Control

of type-2 fuzzy logic systems. Uncertainty is an inherent part of intelligent systems used in real world applications. Conventional controllers;

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Type 2 Fuzzy Neural Networks and Their Applications

This book deals with the theory, design principles, and application of hybrid intelligent systems using type-2 fuzzy sets in combination;

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Intelligent Control

, another describes a commercially available software system for developing fuzzy logic application. Intelligent Control is filled with worked;

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Extension of the Fuzzy Sugeno Integral Based on Generalized Type-2 Fuzzy Logic

fuzzy logic. This extension enables it to handle higher levels of uncertainty when adding any number of sources and types of information in a;

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Recent Advances on Hybrid Approaches for Designing Intelligent Systems

applications for type-2 fuzzy systems. The second part contains papers with the main theme of bio-inspired optimization algorithms, which are basically;

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Industrial Intelligent Control

as neural networks, fuzzy logic, ruled based, and genetic algorithms. Demonstrates how to develop, design and use intelligent systems to;

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Introduction To Type-2 Fuzzy Logic Control

Written by world-class leaders in type-2 fuzzy logic control, this book offers a self-contained reference for both researchers and students;

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Intuitionistic and Type-2 Fuzzy Logic Enhancements in Neural and Optimization Algorithms

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

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Soft Computing with NeuroFuzzy Systems

collaborative applications in robotics using LabVIEW; and adaptive fuzzy sliding mode control scheme for robotic systems.;

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

neural networks, this innovative volume provides a framework for control and modeling of uncertain nonlinear systems with applications to;

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Intelligent Control Systems With Labview(Tm)

Intelligent Control with LabVIEW (TM) is a fresh and pragmatic approach to the understanding of a subject often clouded by too much;

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Parameter Identification for Induction Motor Drives

Networks and Fuzzy Logic for conditions including speed sensorless control. The techniques discussed in this book could be easily extended to most;

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Uncertain Rule-Based Fuzzy Logic Systems

fuzzy logic to the next level-type-2 fuzzy logic. It presents a complete development of both type-1 and type-2 fuzzy logic systems, showing how;

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Application of Intelligent Techniques

computer science towards improvement of crop productivity. With the advancement of technology, several intelligent techniques are used for that;

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Autonomous Rock Excavation, Intelligent Control Techniques And Experimentation

algorithm. The control method developed here is based on the analysis of human operators' performance; it applies neural networks, fuzzy logic and;

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Nature-inspired Optimization of Type-2 Fuzzy Neural Hybrid Models for Classification in Medical Diagnosis

dynamic parameter adaptation of the bird swarm algorithm using fuzzy inference systems, with the aim of improving its performance. For this;

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