Success in evolutionary computation
Author(s)
Bibliographic Information
Success in evolutionary computation
（Studies in computational intelligence, v. 92）
Springer, c2008
- pbk.
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Note
Includes bibliographical references
Description and Table of Contents
Description
Evolutionary Computation (EC) includes a number of techniques such as Genetic Algorithms which have been used in a diverse range of highly successful applications. This book brings together some of these EC applications in fields including electronics, telecommunications, health, bioinformatics, supply chain and other engineering domains, to give the audience, including both EC researchers and practitioners, a glimpse of this exciting and rapidly-evolving field.
Table of Contents
Theory.- Adaptation of a Success Story in GAs: Estimation-of-Distribution Algorithms for Tree-based Optimization Problems.- The Automated Design of Artificial Neural Networks Using Evolutionary Computation.- A Versatile Surrogate-Assisted Memetic Algorithm for Optimization of Computationally Expensive Functions and its Engineering Applications.- Data Mining and Intelligent Multi-Agent Technologies in Medical Informatics.- Applications.- Evolving Trading Rules.- A Hybrid Genetic Algorithm for the Protein Folding Problem Using the 2D-HP Lattice Model.- Optimal Management of Agricultural Systems.- Evolutionary Electronics: Automatic Synthesis of Analog Circuits by GAs.- Intuitive Visualization and Interactive Analysis of Pareto Sets Applied on Production Engineering System.- Privacy Protection with Genetic Algorithms.- A Revision of Evolutionary Computation Techniques in Telecommunications and An Application for The Network Global Planning Problem.- Survivable Network Design with an Evolution Strategy.- Evolutionary Computations for Design Optimization and Test Automation in VLSI Circuits.- Evolving Cooperative Agents in Economy Market Using Genetic Algorithms.- Optimizing Multiplicative General Parameter Finite Impulse Response Filters Using Evolutionary Computation.- Applying Genetic Algorithms to Optimize the Cost of Multiple Sourcing Supply Chain Systems - An Industry Case Study.
by "Nielsen BookData"