Soft Computing Applications in Industry

  • Editors
  • Bhanu Prasad

Part of the Studies in Fuzziness and Soft Computing book series (STUDFUZZ, volume 226)

Table of contents

  1. Front Matter
  2. Piotr Kulczycki
    Pages 69-91
  3. X. Z. Gao, S. J. Ovaska, X. Wang
    Pages 93-115
  4. Zong Woo Geem
    Pages 117-134
  5. Pawan Lingras, Ming Zhong, Satish Sharma
    Pages 151-163
  6. Jiménez Daniel, Pérez-Uribe Andrés, Satizábal Héctor, Barreto Miguel, Van Damme Patrick, Tomassini Marco
    Pages 247-269
  7. Paulo Gomes, Joel Cordeiro, Pedro Gandola, Nuno Seco
    Pages 271-291
  8. Santiago Ontañón, Kinshuk Mishra, Neha Sugandh, Ashwin Ram
    Pages 293-310
  9. Juan M. Corchado, Javier Bajo, Yanira de Paz
    Pages 311-330
  10. Ram Basnet, Srinivas Mukkamala, Andrew H. Sung
    Pages 373-383
  11. Back Matter

About this book


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.


Markov Markov model Statistica algorithm algorithms artificial immune system artificial neural network bioinformatics differential evolution evolution fuzzy hidden Markov model neural networks optimization sensing

Bibliographic information

  • DOI
  • Copyright Information Springer-Verlag Berlin Heidelberg 2008
  • Publisher Name Springer, Berlin, Heidelberg
  • eBook Packages Engineering Engineering (R0)
  • Print ISBN 978-3-540-77464-8
  • Online ISBN 978-3-540-77465-5
  • Series Print ISSN 1434-9922
  • Series Online ISSN 1860-0808
  • Buy this book on publisher's site
Industry Sectors
IT & Software
Oil, Gas & Geosciences