文章基本信息

标题：LEAST SQUARE SUPPORT VECTOR MACHINE FOR DETECTION OF TECSEISMO- IONOSPHERIC ANOMALIES ASSOCIATED WITH THE POWERFUL NEPAL EARTHQUAKE (M_w = 7.5) OF 25 APRIL 2015
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作者：M. Akhoondzadeh
期刊名称：ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences
印刷版ISSN：2194-9042
电子版ISSN：2194-9050
出版年度：2016
卷号：III-8
页码：3-11
出版社：Copernicus Publications
摘要：Due to the irrepalable devastations of strong earthquakes, accurate anomaly detection in time series of different precursors for creating a trustworthy early warning system has brought new challenges. In this paper the predictability of Least Square Support Vector Machine (LSSVM) has been investigated by forecasting the GPS-TEC (Total Electron Content) variations around the time and location of Nepal earthquake. In 77 km NW of Kathmandu in Nepal (28.147° N, 84.708° E, depth = 15.0 km) a powerful earthquake of M_w = 7.8 took place at 06:11:26 UTC on April 25, 2015. For comparing purpose, other two methods including Median and ANN (Artificial Neural Network) have been implemented. All implemented algorithms indicate on striking TEC anomalies 2 days prior to the main shock. Results reveal that LSSVM method is promising for TEC sesimo-ionospheric anomalies detection.
关键词：Ionosphere; TEC; earthquake; anomaly; LSSVM