• ISSN 1003-3238
  • CN 10-1702/P

基于计算智能技术的巴基斯坦北部地区地震活动性预测

K. M. Asim M. Awais F. Martínez-Álvarez T. Iqbal 张盛峰 宋潇潇 白玲

引用本文:
Citation:

基于计算智能技术的巴基斯坦北部地区地震活动性预测

  • 基金项目:

    本译文由中国地震科学实验场(CSES)、山东省重点研发计划(2018GSF120002)及山东省地震局青年基金(JJ1808Y)项目共同资助

  • 摘要: 本文针对巴基斯坦北部地区进行了地震预测研究。研究方法包含了地震学和计算智能技术领域不同学科的交叉融合。针对历史地震活动计算了8种地震学参数。通过计算它们的信息增益来评估这8种参数的预测效能,进而选择了其中6种应用于预测试验。基于这6种参数发展了多个计算智能模型用于预测试验。这些模型包括前馈神经网络、循环神经网络、随机森林、多层感知、径向基神经网络和支持向量机。本文评估了每一种模型的效能,同时利用McNemar统计检验方法来研究计算方法的统计显著性。前馈神经网络模型在巴基斯坦北部地区可表现出统计显著性为75%准确率和78%正确预报的预测结果。
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出版历程

基于计算智能技术的巴基斯坦北部地区地震活动性预测

基金项目:  本译文由中国地震科学实验场(CSES)、山东省重点研发计划(2018GSF120002)及山东省地震局青年基金(JJ1808Y)项目共同资助

摘要: 本文针对巴基斯坦北部地区进行了地震预测研究。研究方法包含了地震学和计算智能技术领域不同学科的交叉融合。针对历史地震活动计算了8种地震学参数。通过计算它们的信息增益来评估这8种参数的预测效能,进而选择了其中6种应用于预测试验。基于这6种参数发展了多个计算智能模型用于预测试验。这些模型包括前馈神经网络、循环神经网络、随机森林、多层感知、径向基神经网络和支持向量机。本文评估了每一种模型的效能,同时利用McNemar统计检验方法来研究计算方法的统计显著性。前馈神经网络模型在巴基斯坦北部地区可表现出统计显著性为75%准确率和78%正确预报的预测结果。

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