Intelligent Systems: 1st Edition (Paperback) book cover

Intelligent Systems

1st Edition

Edited by Bogdan M. Wilamowski, J. David Irwin

CRC Press

610 pages | 357 B/W Illus.

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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

Subject Categories

BISAC Subject Codes/Headings:
TECHNOLOGY & ENGINEERING / Electronics / General