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Application of Soft Computing and Intelligent Methods in Geophysics

  • Alireza Hajian
  • Peter Styles

Part of the Springer Geophysics book series (SPRINGERGEOPHYS)

Table of contents

  1. Front Matter
    Pages i-xvii
  2. Neural Networks

    1. Front Matter
      Pages 1-1
    2. Alireza Hajian, Peter Styles
      Pages 3-69
    3. Alireza Hajian, Peter Styles
      Pages 71-198
  3. Fuzzy Logic

    1. Front Matter
      Pages 199-199
    2. Alireza Hajian, Peter Styles
      Pages 201-300
    3. Alireza Hajian, Peter Styles
      Pages 301-371
  4. Combination of Neural Networks and Fuzzy Logic

    1. Front Matter
      Pages 373-373
    2. Alireza Hajian, Peter Styles
      Pages 375-415
    3. Alireza Hajian, Peter Styles
      Pages 417-484
  5. Genetic Algorithm

    1. Front Matter
      Pages 485-485
    2. Mrinal K. Sen, Subhashis Mallick
      Pages 487-533

About this book

Introduction

This book provides a practical guide to applying soft-computing methods to interpret geophysical data. It discusses the design of neural networks with Matlab for geophysical data, as well as fuzzy logic and neuro-fuzzy concepts and their applications. In addition, it describes genetic algorithms for the automatic and/or intelligent processing and interpretation of geophysical data.

Keywords

Neural Network Neuro-Fuzzy Genetic Algorithm Ground Penetrating Radar Very Low Frequency Electromagnetics

Authors and affiliations

  • Alireza Hajian
    • 1
  • Peter Styles
    • 2
  1. 1.Department of PhysicsNajafabad Branch, Islamic Azad UniversityNajafabadIran
  2. 2.Applied & Environmental Geophysics Research Group, School of Physical and Geographical SciencesKeele UniversityKeeleUnited Kingdom

Bibliographic information

  • DOI https://doi.org/10.1007/978-3-319-66532-0
  • Copyright Information Springer International Publishing AG, part of Springer Nature 2018
  • Publisher Name Springer, Cham
  • eBook Packages Earth and Environmental Science
  • Print ISBN 978-3-319-66531-3
  • Online ISBN 978-3-319-66532-0
  • Series Print ISSN 2364-9127
  • Series Online ISSN 2364-9119
  • Buy this book on publisher's site