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Soft Computing Applications In Industry 1st Edition B V Babu

  • SKU: BELL-4192732
Soft Computing Applications In Industry 1st Edition B V Babu
$ 31.00 $ 45.00 (-31%)

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Soft Computing Applications In Industry 1st Edition B V Babu instant download after payment.

Publisher: Springer-Verlag Berlin Heidelberg
File Extension: PDF
File size: 11.96 MB
Pages: 385
Author: B. V. Babu, Rakesh Angira (auth.), Bhanu Prasad (eds.)
ISBN: 9783540774648, 9783540774655, 3540774645, 3540774653
Language: English
Year: 2008
Edition: 1

Product desciption

Soft Computing Applications In Industry 1st Edition B V Babu by B. V. Babu, Rakesh Angira (auth.), Bhanu Prasad (eds.) 9783540774648, 9783540774655, 3540774645, 3540774653 instant download after payment.

Softcomputing techniques play a vital role in the industry. This book presents several important papers contributed by some of the well-known scientists from all over the globe. The application domains discussed in this book include: agroecology, bioinformatics, branched fluid-transport network layout design, dam scheduling, data analysis and exploration, detection of phishing attacks, distributed terrestrial transportation, fault detection of motors, fault diagnosis of electronic circuits, fault diagnosis of power distribution systems, flood routing, hazard sensing, health care, industrial chemical processes, knowledge management in software development, local multipoint distribution systems, missing data estimation, parameter calibration of rainfall intensity models, parameter identification for systems engineering, petroleum vessel mooring, query answering in P2P systems, real-time strategy games, robot control, satellite heat pipe design, monsoon rainfall forecasting, structural design, tool condition monitoring, vehicle routing, water network design, etc.

The softcomputing techniques presented in this book are on (or closely related to): ant-colony optimization, artificial immune systems, artificial neural networks, Bayesian models, case-based reasoning, clustering techniques, differential evolution, fuzzy classification, fuzzy neural networks, genetic algorithms, harmony search, hidden Markov models, locally weighted regression analysis, probabilistic principal component analysis, relevance vector machines, self-organizing maps, other machine learning and statistical techniques, and the combinations of the above techniques.

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