Soft Computing in Engineering Design and Manufacturing

  • P. K. Chawdhry
  • R. Roy
  • R. K. Pant

Table of contents

  1. Front Matter
    Pages I-XIX
  2. Evolutionary Computing

    1. Front Matter
      Pages 1-1
    2. I. De Falco, A. Della Cioppa, P. Natale, E. Tarantino
      Pages 3-12
    3. W. B. Langdon, R. Poli
      Pages 13-22
    4. Marcin Chady, Riccardo Poli
      Pages 40-47
    5. Vladimír Kvasnièka, Jiøí Pospíchal
      Pages 48-56
  3. Neural Networks

    1. Front Matter
      Pages 57-57
    2. Kwok Ching Tsui, Mark Plumbley
      Pages 69-78
    3. Michael Blumenstein, Brijesh Verma
      Pages 79-83
    4. G. E. Stavroulakis, A. V. Avdelas, P. D. Panagiotopoulos, K. M. Abdalla
      Pages 84-92
    5. Byoung-Tak Zhang, Je-Gun Joung
      Pages 93-101
  4. Fuzzy Logic

    1. Front Matter
      Pages 103-103
    2. Wallace E. Kelly, John H. Painter
      Pages 105-113
    3. F. Abbattista, G. Castellano, A. M. Fanelli
      Pages 114-121
    4. Jan Jantzen, Mariagrazia Dotoli
      Pages 122-130
    5. A. B. Patki, G. V. Raghunathan, Azar Khurshid
      Pages 131-140
    6. Tadashi Iokibe
      Pages 141-150

About these proceedings

Introduction

Soft Computing has emerged as an important approach towards achieving intelligent computational paradigms where key elements are learning from experience in the presence of uncertainties, fuzzy belief functioos, and ·evolutioo of the computing strategies of the learning agent itself. Fuzzy, neural and evolutionary computing are the three major themes of soft computing. The book presents original research papers dealing with the theory of soft computing and its applicatioos in engineering design and manufacturing. The methodologies have been applied to a large variety of real life problems. Applicatioo of soft computing has provided the opportunity to integrate human like 'vagueness' and real life 'uncertainty' to an otherwise 'hard' computer programme. Now, a computer programme can learn, adapt, and evolve using soft computing. The book identifies the strengths and Iimitatioos of soft cOOlputing techniques, particularly with reference to their engineering applications. The applications range fran design optimisatioo to scheduling and image analysis. Goal optimisatioo with incomplete infmnatioo and under uncertainty is the key to solving real-life problems in design and manufacturing. Soft computing techniques presented in this book address these issues. Computatiooal complexity and efficient implementatioo of these techniques are also major concerns for realising useful industrial applications of soft computing. The different parts in the book also address these issues. The book cootains 9 parts, 8 of which are based 00 papers fran the '2nd On-line World Conference 00 Soft Computing in Engineering Design and Manufacture (WSC2),.

Keywords

Scheduling artificial neural network cognition evolution evolutionary algorithm genetic programming information mutation neural network operating system optimization pattern recognition robot robotics simulation

Editors and affiliations

  • P. K. Chawdhry
    • 1
  • R. Roy
    • 2
  • R. K. Pant
    • 3
  1. 1.School of Mechanical EngineeringUniversity of BathBathUK
  2. 2.The CIM InstituteCranfield UniversityCranfieldUK
  3. 3.Department of Aerospace EngineeringIndian Institute of TechnologyPowaiIndia

Bibliographic information

  • DOI https://doi.org/10.1007/978-1-4471-0427-8
  • Copyright Information Springer-Verlag London Limited 1998
  • Publisher Name Springer, London
  • eBook Packages Springer Book Archive
  • Print ISBN 978-3-540-76214-0
  • Online ISBN 978-1-4471-0427-8
  • About this book