Studies in Fuzziness and Soft Computing

Analysis and Design

By: Oscar Castillo (Editor), Patricia Melin (Editor)

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Hardcover | 31 October 2006

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Hardcover
452 Pages

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23.5 x 15.88 x 1.91

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We describe in this book, new methods for analysis and design of hybrid intelligent systems using soft computing techniques. Soft Computing (SC) consists of several computing paradigms, including fuzzy logic, neural networks, and genetic algorithms, which can be used to produce powerful hybrid intelligent systems for solving problems in pattern recognition, time series prediction, intelligent control, robotics and automation. Hybrid int- ligent systems that combine several SC techniques are needed due to the complexity and high dimensionality of real-world problems. Hybrid int- ligent systems can have different architectures, which have an impact on the efficiency and accuracy of these systems, for this reason it is very - portant to optimize architecture design. The architectures can combine, in different ways, neural networks, fuzzy logic and genetic algorithms, to achieve the ultimate goal of pattern recognition, time series prediction, - telligent control, or other application areas. This book is intended to be a major reference for scientists and en- neers interested in applying new computational and mathematical tools to design hybrid intelligent systems. This book can also be used as a textbook or major reference for graduate courses like the following: soft computing, intelligent pattern recognition, computer vision, applied artificial intel- gence, and similar ones. We consider that this book can also be used to get novel ideas for new lines of research, or to continue the lines of research proposed by the authors of the book.

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You Can Find This Book In

Non-Fiction Computing & I.T.Computer Science Artificial Intelligence Neural Networks & Fuzzy Systems Computer Hardware Reference, Information & Interdisciplinary Subjects Research & Information Information theory Cybernetics & Systems Theory Expert Systems & Knowledge-Based Systems Mathematics

Applied Mathematics Engineering & Technology Technology in General Engineering in General

Hybridization schemes in architectures of computational intelligence	p. 3
Boltzmann machines learning using high order decimation	p. 21
Evolutionary optimization of a Wiener model	p. 43
Synchronization of chaotic neural networks : a generalized Hamiltonian systems approach	p. 59
Mediative fuzzy logic : a novel approach for handling contradictory knowledge	p. 75
Direct and indirect adaptive neural control of NonLinear systems	p. 95
Simple tuning of fuzzy controllers	p. 115
From type-1 to type-2 fuzzy logic control : a stability and robustness study	p. 135
A comparative study of controllers using type-2 and type-1 fuzzy logic	p. 151
Evolutionary computing for topology optimization of type-2 fuzzy controllers	p. 163
Decision trees and CBR for the navigation system of a CNN-based autonomous robot	p. 181
Intelligent agents in distributed fault tolerant systems	p. 203
Genetic path planning with fuzzy logic adaptation for rovers traversing rough terrain	p. 215
Chattering attenuation using linear-in-the-parameter neural nets in variable structure control of robot manipulators with friction	p. 229
Tracking control for a unicycle mobile robot using a fuzzy logic controller	p. 243
Intelligent control and planning of autonomous mobile robots using fuzzy logic and genetic algorithms	p. 255
The role of neural networks in the interpretation of antique handwritten documents	p. 269
Object recognition using fuzzy inferential reasoning	p. 283
The fuzzy Sugeno integral as a decision operator in the recognition of images with modular neural networks	p. 299
Modular neural networks and fuzzy Sugeno integral for pattern recognition : the case of human face and fingerprint	p. 311
Optimal training for associative memories : application to fault diagnosis in fossil electric power plants	p. 329
Acceleration output prediction of buildings using a polynomial artificial neural network	p. 357
Time series forecasting of tomato prices in Mexico using modular neural networks and processing in parallel	p. 385
Modular neural networks with fuzzy Sugeno integration applied to time series prediction	p. 403
On linguistic summaries of time series using a fuzzy quantifier based aggregation via the Sugeno integral	p. 415
Table of Contents provided by Blackwell. All Rights Reserved.

Studies in Fuzziness and Soft Computing

Analysis and Design

At a Glance

Hardcover

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Defective items

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