Authors:
- Combines materials sciences with deep machine learning to develop new methods for earthquake prediction testing
- Introduces recent AI modeling using a Keras–TensorFlow environment
- Allows readers to learn methods of comprehensive investigation of materials science and data-driven science
Part of the book series: Advances in Geological Science (AGS)
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Table of contents (8 chapters)
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Front Matter
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Back Matter
About this book
Authors and Affiliations
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Kamakura, Japan
Mitsuhiro Toriumi
About the author
Bibliographic Information
Book Title: Geochemical Mechanics and Deep Neural Network Modeling
Book Subtitle: Applications to Earthquake Prediction
Authors: Mitsuhiro Toriumi
Series Title: Advances in Geological Science
DOI: https://doi.org/10.1007/978-981-19-3659-3
Publisher: Springer Singapore
eBook Packages: Earth and Environmental Science, Earth and Environmental Science (R0)
Copyright Information: The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2022
Hardcover ISBN: 978-981-19-3658-6Published: 20 August 2022
Softcover ISBN: 978-981-19-3661-6Published: 21 August 2023
eBook ISBN: 978-981-19-3659-3Published: 19 August 2022
Series ISSN: 2524-3829
Series E-ISSN: 2524-3837
Edition Number: 1
Number of Pages: XIII, 274
Number of Illustrations: 14 b/w illustrations, 209 illustrations in colour
Topics: Geochemistry, Geophysics/Geodesy, Machine Learning, Mathematics of Planet Earth, Natural Hazards