1st Edition

Intelligent Systems

Edited By Bogdan M. Wilamowski, J. David Irwin Copyright 2011
    610 Pages 357 B/W Illustrations
    by CRC Press

    610 Pages 357 B/W Illustrations
    by CRC Press

    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:

    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


    Bogdan M. Wilamowski, J. David Irwin