Overview
- Easy to understand step-by-step description of the principles of soft computing methods to interpret geophysical data
- Provides a guide to use Matlab to apply soft computing methods
- Includes various practical examples with interesting engineering applications
Part of the book series: Springer Geophysics (SPRINGERGEOPHYS)
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Table of contents (7 chapters)
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Front Matter
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Neural Networks
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Front Matter
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Fuzzy Logic
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Front Matter
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Combination of Neural Networks and Fuzzy Logic
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Front Matter
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Genetic Algorithm
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Front Matter
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Keywords
About this book
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.
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Authors and Affiliations
Bibliographic Information
Book Title: Application of Soft Computing and Intelligent Methods in Geophysics
Authors: Alireza Hajian, Peter Styles
Series Title: Springer Geophysics
DOI: https://doi.org/10.1007/978-3-319-66532-0
Publisher: Springer Cham
eBook Packages: Earth and Environmental Science, Earth and Environmental Science (R0)
Copyright Information: Springer International Publishing AG, part of Springer Nature 2018
Hardcover ISBN: 978-3-319-66531-3Published: 05 July 2018
Softcover ISBN: 978-3-030-09774-5Published: 12 January 2019
eBook ISBN: 978-3-319-66532-0Published: 21 June 2018
Series ISSN: 2364-9119
Series E-ISSN: 2364-9127
Edition Number: 1
Number of Pages: XVII, 533
Number of Illustrations: 163 b/w illustrations, 247 illustrations in colour
Topics: Geophysics/Geodesy, Geotechnical Engineering & Applied Earth Sciences, Mathematical Applications in the Physical Sciences, Math Applications in Computer Science, Artificial Intelligence