Applicability of artificial intelligence to reservoir induced earthquakes

• Autorzy: Samui P. , Kim D.

Identyfikatory

DOI

10.2478/s11600-014-0201-1

• Języki publikacji: EN

Abstrakty

EN

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.

Słowa kluczowe

EN

earthquake; prediction; support vector machine (SVM); least square

PL

trzęsienie ziemi; prognoza; maszyna wektorów nośnych

• Wydawca: Instytut Geofizyki PAN ; Springer
• Czasopismo: Acta Geophysica
• Rocznik: 2014
• Tom: Vol. 62, no. 3
• Strony: 608--619
• Opis fizyczny: Bibliogr. 23 poz.

Twórcy

autor

Samui P.

• Centre for Disaster Mitigation and Management, VIT University, Vellore, India

autor

Kim D.

• Department of Civil Engineering, Kunsan National University, Kunsan, Jeonbuk, South Korea

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