Advances in Machine Learning and Data Analysis

  • Mahyar A. Amouzegar
Part of the Lecture Notes in Electrical Engineering book series (LNEE, volume 48)

Table of contents

  1. Front Matter
    Pages i-viii
  2. Seyed Eghbal Ghobadi, Omar Edmond Loepprich, Oliver Lottner, Klaus Hartmann, Wolfgang Weihs, Otmar Loffeld
    Pages 1-13
  3. Q. Meng, M. H. Lee, C. J. Hinde
    Pages 15-26
  4. Dejun Xie, David Edwards, Giberto Schleiniger
    Pages 79-94
  5. V. Díaz Casás, P. Porca Belío, F. López Peña, R. J. Duro
    Pages 139-149
  6. Quoc Kien Vuong, Se-Hwan Yun, Suki Kim
    Pages 165-178
  7. Mohammad Golkhah, Mohammad Tavakoli Bina
    Pages 191-202
  8. Jan Broer, Tim Wendisch, Nina Willms
    Pages 203-215
  9. Nathan Percival, Jennifer Percival, Clemens Martin
    Pages 217-230
  10. Scott A. Jeffrey, Brian Cozzarin
    Pages 231-239

About this book

Introduction

A large international conference on Advances in Machine Learning and Data Analysis was held in UC Berkeley, California, USA, October 22-24, 2008, under the auspices of the World Congress on Engineering and Computer Science (WCECS 2008). This volume contains sixteen revised and extended research articles written by prominent researchers participating in the conference. Topics covered include Expert system, Intelligent decision making, Knowledge-based systems, Knowledge extraction, Data analysis tools, Computational biology, Optimization algorithms, Experiment designs, Complex system identification, Computational modeling, and industrial applications. Advances in Machine Learning and Data Analysis offers the state of the art of tremendous advances in machine learning and data analysis and also serves as an excellent reference text for researchers and graduate students, working on machine learning and data analysis.

Keywords

Computational Modelling Database Management Fuzzy Systems Intelligent Decision Making Optimization Algorithms data analysis machine learning

Editors and affiliations

  • Mahyar A. Amouzegar
    • 1
  1. 1.Dept. Chemical EngineeringCalifornia State UniversityLong BeachUSA

Bibliographic information

  • DOI https://doi.org/10.1007/978-90-481-3177-8
  • Copyright Information Springer Science+Business Media B.V. 2010
  • Publisher Name Springer, Dordrecht
  • eBook Packages Engineering
  • Print ISBN 978-90-481-3176-1
  • Online ISBN 978-90-481-3177-8
  • Series Print ISSN 1876-1100
  • Series Online ISSN 1876-1119