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Springer Evolutionary Algorithms and Neural Networks Book

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Description

Explore the intersection of computational intelligence with this Springer publication. This book provides a foundation in artificial neural networks with a specific focus on evolutionary algorithms. Readers can examine a literature review of established methods such as genetic algorithms, particle swarm optimization, ant colony optimization, and biogeography-based optimization. The text proposes evolutionary versions of several neural network architectures. These include feed forward neural networks, radial basis function networks, recurrent neural networks, and multi-layer perceptrons. This resource serves as a technical guide for understanding the integration of evolutionary computation with neural network structures.

Key Features

This Springer book covers the fundamentals of artificial neural networks and evolutionary algorithms.

The text includes a literature review of particle swarm and ant colony optimization methods.

Learn about genetic algorithms and biogeography-based optimization within this volume.

The content proposes evolutionary versions of feed forward and radial basis function networks.

Detailed sections cover recurrent neural networks and multi-layer perceptron architectures.

Product Specifications

Format
hardcover
Domain
Amazon UK
Release Date
12 July 2018
Listed Since
01 May 2018

Barcode

No barcode data available

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