Applicability of artificial intelligence to reservoir induced earthquakes |
| |
| Authors: | Pijush Samui Dookie Kim |
| |
| Institution: | 1. Centre for Disaster Mitigation and Management, VIT University, Vellore, India
2. Department of Civil Engineering, Kunsan National University, Kunsan, Jeonbuk, South Korea
|
| |
| Abstract: | This paper proposes to use least square support vector machine (LSSVM) and relevance vector machine (RVM) for prediction of the magnitude (M) of induced earthquakes based on reservoir parameters. Comprehensive parameter (E) and maximum reservoir depth (H) are used as input variables of the LSSVM and RVM. The output of the LSSVM and RVM is M. Equations have been presented based on the developed LSSVM and RVM. The developed RVM also gives variance of the predicted M. A comparative study has been carried out between the developed LSSVM, RVM, artificial neural network (ANN), and linear regression models. Finally, the results demonstrate the effectiveness and efficiency of the LSSVM and RVM models. |
| |
| Keywords: | |
| 本文献已被 SpringerLink 等数据库收录！ |
|
