Ulster University Logo

Seismic Anomaly Detection in Time Series Electromagnetic Data by the SWARM Satellites

Christodoulou, Vyron, Bi, Yaxin and Zhao, Gouge (2015) Seismic Anomaly Detection in Time Series Electromagnetic Data by the SWARM Satellites. In: In: Dragon 3 symposium. ESA Communication. ESA SP-724. 1 pp. [Conference contribution]

[img] Text - Accepted Version


It has been hypothesized that electromagnetic (EM) anomalies act as precursors to seismic ac- tivities. More recently, there have been a lot of studies regarding seismic events and their possi- ble link with EM sequential anomalies from dif- ferent sources. A lot of work has been done such as in [1], where statistical methods have been used to prove this connection. Machine learning (ML) methods were used in [2] . Here, to ana- lyze the data we use simple and computationally e cient methods. The two proposed methods, a novel variant of Cumulative Sum (CUSUM) with Exponentially Weighted Moving Average (EWMA) and a Fuzzy Inspired Approach are evaluated under new EM observations by the SWARM satellites. Speci cally we are investi- gating two seismic events occurred on the 6th of December at 02:43 and 18:20 respectively and their possible causal links with EM anomalies.

Item Type:Conference contribution (Poster)
Keywords:Seismic Anomaly Detection, Electromagnetic Data, SWARM Satellites
Faculties and Schools:Faculty of Computing & Engineering
Faculty of Computing & Engineering > School of Computing and Mathematics
Research Institutes and Groups:Computer Science Research Institute
Computer Science Research Institute > Artificial Intelligence and Applications
ID Code:38993
Deposited By: Dr Yaxin Bi
Deposited On:15 Nov 2017 15:12
Last Modified:15 Nov 2017 15:12

Repository Staff Only: item control page