Soft Computing in Artificial Intelligence (Paperback, 2014 ed.)

This book explores the concept of artificial intelligence based on knowledge-based algorithms. Given the current hardware and software technologies and artificial intelligence theories, we can think of how efficient to provide a solution, how best to implement a model and how successful to achieve it. This edition provides readers with the most recent progress and novel solutions in artificial intelligence. This book aims at presenting the research results and solutions of applications in relevance with artificial intelligence technologies. We propose to researchers and practitioners some methods to advance the intelligent systems and apply artificial intelligence to specific or general purpose. This book consists of 13 contributions that feature fuzzy (r, s)-minimal pre- and -open sets, handling big coocurrence matrices, Xie-Beni-type fuzzy cluster validation, fuzzy c-regression models, combination of genetic algorithm and ant colony optimization, building expert system, fuzzy logic and neural network, individual role adaptation for team sports, application of polynomial neural networks, recursive neuro-fuzzy algorithm for water management, application of interactive genetic algorithm, and Artificial Neural Network (ANN) model. This edition is published in original, peer reviewed contributions covering from initial design to final prototypes and verification.

General

Imprint:	Springer International Publishing AG
Country of origin:	Switzerland
Series:	Advances in Intelligent Systems and Computing, 270
Release date:	March 2014
First published:	2014
Editors:	Young Im Cho
Volume editors:	Dong-Han Kim
Editors:	Eric T Matson
Dimensions:	235 x 155 x 9mm (L x W x T)
Format:	Paperback
Pages:	153
Edition:	2014 ed.
ISBN-13:	978-3-319-05514-5
Categories:	Books > Computing & IT > Applications of computing > Artificial intelligence > General
LSN:	3-319-05514-3
Barcode:	9783319055145

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