東華大學圖書館 |

語系: 繁體中文

說明(常見問題)

回圖書館首頁

手機版館藏查詢

登入

回首頁 到查詢結果 [ subject:"Seismology- Data processing." ]

切換: 標籤 | MARC模式 | ISBD

Global seismicity dynamics and data-...

Toriumi, Mitsuhiro.

FindBook

Google Book

Amazon

博客來

Global seismicity dynamics and data-driven science = seismicity modelling by big data analytics /

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Global seismicity dynamics and data-driven science/ by Mitsuhiro Toriumi.
其他題名:	seismicity modelling by big data analytics /
作者:	Toriumi, Mitsuhiro.
出版者:	Singapore :Springer Singapore : : 2021.,
面頁冊數:	ix, 231 p. :ill., digital ;24 cm.
內容註:	- Introduction -- Nature of Earthquakes in the Solid Earth -- Global Seismicity of the Solid Earth -- Data - Driven Sciences for Geosciences -- Data-Driven Science of Seismicity -- Down Scaling Seismicity of Japanese Regions -- Correlated Seismicity of the Northern California Region -- Model of Seismicity Dynamics from Data-Driven Science -- Seismicity Dynamics Model of Global Earth and Japanese Island Region -- Predictive Modeling of Global and Regional Seismicity Rates -- Future Problems of Prediction of Giant Plate Boundary Earthquakes -- Application of Recurrent Neural Network (RNN) Modeling for Global Seismicity Dynamics -- Comments on Databases and Software Used in This Book.
Contained By:	Springer Nature eBook
標題:	Seismology - Data processing. -
電子資源:	https://doi.org/10.1007/978-981-15-5109-3
ISBN:	9789811551093

Global seismicity dynamics and data-driven science = seismicity modelling by big data analytics /
Toriumi, Mitsuhiro.

Global seismicity dynamics and data-driven scienceseismicity modelling by big data analytics /[electronic resource] :by Mitsuhiro Toriumi. - Singapore :Springer Singapore :2021. - ix, 231 p. :ill., digital ;24 cm. - Advances in geological science,2524-3829. - Advances in geological science..

- Introduction -- Nature of Earthquakes in the Solid Earth -- Global Seismicity of the Solid Earth -- Data - Driven Sciences for Geosciences -- Data-Driven Science of Seismicity -- Down Scaling Seismicity of Japanese Regions -- Correlated Seismicity of the Northern California Region -- Model of Seismicity Dynamics from Data-Driven Science -- Seismicity Dynamics Model of Global Earth and Japanese Island Region -- Predictive Modeling of Global and Regional Seismicity Rates -- Future Problems of Prediction of Giant Plate Boundary Earthquakes -- Application of Recurrent Neural Network (RNN) Modeling for Global Seismicity Dynamics -- Comments on Databases and Software Used in This Book.

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 dynamic equations 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.

ISBN: 9789811551093

Standard No.: 10.1007/978-981-15-5109-3doiSubjects--Topical Terms:

1085846
Seismology
--Data processing.

LC Class. No.: QE539 / .T67 2021

Dewey Class. No.: 551.22

Global seismicity dynamics and data-driven science = seismicity modelling by big data analytics /
LDR:03390nmm a2200337 a 4500 001 2235373
003 DE-He213
005 20201007183119.0
006 m d
007 cr nn 008maaau
008 211111s2021 si s 0 eng d
020 $a 9789811551093 $q (electronic bk.)
020 $a 9789811551086 $q (paper)
024 7 $a 10.1007/978-981-15-5109-3 $2 doi
035 $a 978-981-15-5109-3
040 $a GP $c GP
041 0 $a eng
050 4 $a QE539 $b .T67 2021
072 7 $a PHVG $2 bicssc
072 7 $a SCI032000 $2 bisacsh
072 7 $a PHVG $2 thema
082 0 4 $a 551.22 $2 23
090 $a QE539 $b .T683 2021
100 1 $a Toriumi, Mitsuhiro. $3 3485784
245 1 0 $a Global seismicity dynamics and data-driven science $h [electronic resource] : $b seismicity modelling by big data analytics / $c by Mitsuhiro Toriumi.
260 $a Singapore : $b Springer Singapore : $b Imprint: Springer, $c 2021.
300 $a ix, 231 p. : $b ill., digital ; $c 24 cm.
490 1 $a Advances in geological science, $x 2524-3829
505 0 $a - Introduction -- Nature of Earthquakes in the Solid Earth -- Global Seismicity of the Solid Earth -- Data - Driven Sciences for Geosciences -- Data-Driven Science of Seismicity -- Down Scaling Seismicity of Japanese Regions -- Correlated Seismicity of the Northern California Region -- Model of Seismicity Dynamics from Data-Driven Science -- Seismicity Dynamics Model of Global Earth and Japanese Island Region -- Predictive Modeling of Global and Regional Seismicity Rates -- Future Problems of Prediction of Giant Plate Boundary Earthquakes -- Application of Recurrent Neural Network (RNN) Modeling for Global Seismicity Dynamics -- Comments on Databases and Software Used in This Book.
520 $a 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 dynamic equations 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.
650 0 $a Seismology $x Data processing. $3 1085846
650 0 $a Big data. $3 2045508
650 1 4 $a Geophysics/Geodesy. $3 891016
650 2 4 $a Mathematics of Planet Earth. $3 3236712
650 2 4 $a Natural Hazards. $3 1005730
650 2 4 $a Big Data. $3 3134868
710 2 $a SpringerLink (Online service) $3 836513
773 0 $t Springer Nature eBook
830 0 $a Advances in geological science. $3 3377883
856 4 0 $u https://doi.org/10.1007/978-981-15-5109-3
950 $a Earth and Environmental Science (SpringerNature-11646)