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利用支持向量机和高斯过程回归测定水库诱发的地震(英文)

Determination of reservoir induced earthquake using support vector machine and gaussian process regression

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【作者】 Pijush SamuiDookie Kim

【Author】 Pijush Samui 1,2 and Dookie Kim 21.Centre for Disaster Mitigation and Management,VIT University,Vellore,632014,India.2.Department of Civil Engineering,Kunsan National University,Kunsan,Jeonbuk,South Korea.

【机构】 Centre for Disaster Mitigation and Management,VIT UniversityDepartment of Civil Engineering,Kunsan National University

【摘要】 水库诱发地震震级(M)的预测是在地震工程中的一项重要任务。本文采用支持向量机(SVM)和高斯过程回归(GPR)模型根据水库的参数预测了水库诱发地震震级(M)。综合参数(E)和最大的水库深度(H)作为支持向量机和高斯过程回归模型的输入参数。我们给出一个方程确定水库诱发地震震级(M)。将本文开发的支持向量机和建立的高斯过程回归方法与人工神经网络(ANN)方法相比。结果表明,本文研发的支持向量机和高斯过程回归方法是预测水库诱发地震震级(M)的有效工具。

【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.

  • 【文献出处】 Applied Geophysics ,应用地球物理(英文版) , 编辑部邮箱 ,2013年02期
  • 【分类号】TP18;P315.6
  • 【下载频次】105
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