Intelligent Systems  book cover
1st Edition

Intelligent Systems

ISBN 9781138071889
Published November 22, 2017 by CRC Press
610 Pages 357 B/W Illustrations

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Book Description

The Industrial Electronics Handbook, Second Edition combines traditional and newer, more specialized knowledge that will help industrial electronics engineers develop practical solutions for the design and implementation of high-power applications. Embracing the broad technological scope of the field, this collection explores fundamental areas, including analog and digital circuits, electronics, electromagnetic machines, signal processing, and industrial control and communications systems. It also facilitates the use of intelligent systems—such as neural networks, fuzzy systems, and evolutionary methods—in terms of a hierarchical structure that makes factory control and supervision more efficient by addressing the needs of all production components.

Enhancing its value, this fully updated collection presents research and global trends as published in the IEEE Transactions on Industrial Electronics Journal, one of the largest and most respected publications in the field.

As intelligent systems continue to replace and sometimes outperform human intelligence in decision-making processes, they have made substantial contributions to the solution of very complex problems. As a result, the field of computational intelligence has branched out in several directions. For instance, artificial neural networks can learn how to classify patterns, such as images or sequences of events, and effectively model complex nonlinear systems. Simple and easy to implement, fuzzy systems can be applied to successful modeling and system control.

Illustrating how these and other tools help engineers model nonlinear system behavior, determine and evaluate system parameters, and ensure overall system control, Intelligent Systems:

  • Addresses various aspects of neural networks and fuzzy systems
  • Focuses on system optimization, covering new techniques such as evolutionary methods, swarm, and ant colony optimizations
  • Discusses several applications that deal with methods of computational intelligence

Other volumes in the set:

Table of Contents

Introduction to Intelligent Systems
Backpropagation to Neurocontrol
Neural Network Based Control
Fuzzy Logic Controllers
Neural Networks
Understanding Neural Networks
Neural Network Architectures
The Radial Basis Function Type of Neural Network and its Implementations in Hardware
GMDH Neural Networks
Optimization of Neural Network Architectures
Parity-N problems as a vehicle to compare efficiency of neural network architecture
Neural Network Learning
Levenberg Marquardt Training
NBN algorithm
Accelerating the multilayer perceptron learning algorithms
Pruning algorithms in feedforward neural networks
Principal Component Analysis
Adaptive Critics
Self-Organized Maps
Fuzzy Systems
Fuzzy Logic Based Control
Neuro-Fuzzy systems
Introduction to Type-2 Fuzzy Logic Controllers CA + PV
Fuzzy Pattern Recognition figures extract
The Fuzzy Ant
Multiobjective Optimization Methods CA + PV
Fundamentals of Evolutionary Multi-Objective Optimization
Ant colony optimization
Heuristics for two-dimensional bin-packing problems
Particle Swarm Optimization
Evolutionary Computation
Data Mining
Autonomous mental development
Synthetic Biometrics for Testing Biometric Systems and User Training
Data Mining on Internet By Using PERL

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