Mining Extreme Patterns of Seismic Signals in China Based on Heavy-Tailed Statistics

DOI

10.2991/icitme-18.2018.42How to use a DOI?

Keywords

pattern mining; extreme value theory; risk analysis; heavy-tailed statistics

Abstract

Strong earthquakes are the most violent natural hazards, which have caused huge losses of lives and property to human beings in the last decade. Mining time patterns of seismic events, especially extreme ones, within a specific time window and region, is of great importance to policy making and disaster reduction. In this paper, we apply heavy-tailed statistics in extreme value theory to mining the temporal pattern of seismic events in China and build a computational model. We show that earthquakes of magnitude above Ms. 6.0 in China follow the generalized Pareto distribution. We use the proposed model to simulate the possible risk of extreme seismic magnitude in future time windows. Comparison with real-world records demonstrate the validity of our model.

Copyright

© 2018, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Peng Zhang
AU  - Chunbo Fan
AU  - Yunxia Zhang
AU  - Yi Ding
PY  - 2018/08
DA  - 2018/08
TI  - Mining Extreme Patterns of Seismic Signals in China Based on Heavy-Tailed Statistics
BT  - Proceedings of the 2018 International Conference on Information Technology and Management Engineering (ICITME 2018)
PB  - Atlantis Press
SP  - 209
EP  - 212
SN  - 1951-6851
UR  - https://doi.org/10.2991/icitme-18.2018.42
DO  - 10.2991/icitme-18.2018.42
ID  - Zhang2018/08
ER  -