Global Seismicity Dynamics and Data-Driven Science : Seismicity Modelling by Big Data Analytics

Mitsuhiro Toriumi

ISBN 10: 9811551081 / ISBN 13: 9789811551086

Published by Springer Nature Singapore, Springer Nature Singapore, 2020

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Bibliographic Details

Title: Global Seismicity Dynamics and Data-Driven ...

Publisher: Springer Nature Singapore, Springer Nature Singapore

Publication Date: 2020

Binding: Buch

Condition: Neu

About this title

Synopsis:

The recent explosion of global and regional seismicity data in the world requires new methods of investigation of microseismicity and development of their modelling to understand the nature of whole earth mechanics. In this book, the author proposes a powerful tool to reveal the characteristic features of global and regional microseismicity big data accumulated in the databases of the world. The method proposed in this monograph is based on (1) transformation of stored big data to seismicity density data archives, (2) linear transformation of microseismicity density data matrixes to correlated seismicity matrixes by means of the singular value decomposition method, (3) time series analyses of globally and regionally correlated seismicity rates, and (4) the minimal non-linear equations approximation of their correlated seismicity rate dynamics. Minimal non-linear modelling is the manifestation for strongly correlated seismicity time series controlled by Langevin-type stochastic dynamicequations involving deterministic terms and random Gaussian noises. A deterministic term is composed minimally with correlated seismicity rate vectors of a linear term and of a term with a third exponent. Thus, the dynamics of correlated seismicity in the world contains linearly changing stable nodes and rapid transitions between them with transient states. This book contains discussions of future possibilities of stochastic extrapolations of global and regional seismicity in order to reduce earthquake disasters worldwide. The dataset files are available online and can be downloaded at springer.com.

About the Author:

Mitsuhiro Toriumi is a senior researcher at the Japan Agency of Marine – Earth Science and Technology (JAMSTEC). He was chief scientist of the board of innovation center of JAMSTEC and studied application of data-driven science and machine learning for global and regional seismicity. He was the research director of the Institute for Research on Earth Evolution (IFREE) and a professor in the Department of Complex Science and Engineering and a professor in the Faculty of Science, The University of Tokyo. During his early career, he was an associate professor of the Faculty of Science of Ehime University and an assistant professor of The University of Tokyo. He is an invited professor of the Open University of Japan. He has published and edited several books in the field of petrology, rheology, earth science, and solid earth science. He is a committee member of the Research Organization of Information and Systems of Japan and an adviser in Core Research for Evolutionary Science and Technology (Information and Measurement). He has been awarded the Geological Society of Japan Award.