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From monitoring of seismic fields to the automatic forecasting of earthquakes

Valery Gitis (The Institute for Information Transmission Problems (Russian Academy of Science), Moscow, Russian Federation)
Alexander Derendyaev (The Institute for Information Transmission Problems (Russian Academy of Science), Moscow, Russian Federation)

International Journal of Web Information Systems

ISSN: 1744-0084

Article publication date: 25 June 2019

Issue publication date: 15 October 2019

72

Abstract

Purpose

The purpose of this paper is to offer two Web-based platforms for systematic analysis of seismic processes. Both platforms are designed to analyze and forecast the state of the environment and, in particular, the level of seismic hazard. The first platform analyzes the fields representing the properties of the seismic process; the second platform forecasts strong earthquakes. Earthquake forecasting is based on a new one-class classification method.

Design/methodology/approach

The paper suggests an approach to systematic forecasting of earthquakes and examines the results of tests. This approach is based on a new method of machine learning, called the method of the minimum area of alarm. The method allows to construct a forecast rule that optimizes the probability of detecting target earthquakes in a learning sample set, provided that the area of the alarm zone does not exceed a predetermined one.

Findings

The paper presents two platforms alongside the method of analysis. It was shown that these platforms can be used for systematic analysis of seismic process. By testing of the earthquake forecasting method in several regions, it was shown that the method of the minimum area of alarm has satisfactory forecast quality.

Originality/value

The described technology has two advantages: simplicity of configuration for a new problem area and a combination of interactive easy analysis supported by intuitive operations and a simplified user interface with a detailed, comprehensive analysis of spatio-temporal processes intended for specialists. The method of the minimum area of alarm solves the problem of one-class classification. The method is original. It uses in training the precedents of anomalous objects and statistically takes into account normal objects.

Keywords

Acknowledgements

The paper is partly supported by the Russian Foundation for Basic Research, the project 17-07-00494.

Citation

Gitis, V. and Derendyaev, A. (2019), "From monitoring of seismic fields to the automatic forecasting of earthquakes", International Journal of Web Information Systems, Vol. 15 No. 5, pp. 535-549. https://doi.org/10.1108/IJWIS-12-2018-0087

Publisher

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Emerald Publishing Limited

Copyright © 2019, Emerald Publishing Limited

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