Determination of reservoir induced earthquake using support vector machine and gaussian process regression
Pijush Samui1,2, and Dookie Kim2
1. Centre for Disaster Mitigation and Management, VIT University, Vellore-632014, India
2. Department of Civil Engineering, Kunsan National University, Kunsan, Jeonbuk, South Korea
Abstract The prediction of magnitude (M) of reservoir induced earthquake is an important task in earthquake engineering. In this article, we employ a Support Vector Machine (SVM) and Gaussian Process Regression (GPR) for prediction of reservoir induced earthquake M based on reservoir parameters. Comprehensive parameter (E) and maximum reservoir depth (H) are considered as inputs to the SVM and GPR. We give an equation for determination of reservoir induced earthquake M. The developed SVM and GPR have been compared with the Artificial Neural Network (ANN) method. The results show that the developed SVM and GPR are efficient tools for prediction of reservoir induced earthquake M.
Pijush Samui,and Dookie Kim. Determination of reservoir induced earthquake using support vector machine and gaussian process regression[J]. APPLIED GEOPHYSICS, 2013, 10(2): 229-234.
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2013, Vol. 10 
