Abstract One of the influential components in the probabilistic seismic-hazard analysis (PSHA) is selecting appropriate ground motion prediction equations (GMPEs). To handle the source of epistemic uncertainty, the most common approach is considering several GMPEs in a logic tree framework. In such an approach, the selected GMPEs and the weights assigned for each one are usually determined by experts, mostly according to gut feeling. In order to reduce the role of subjectivity in selecting GMPEs, some statistical criteria based on goodness-of-fit measures were developed in recent years. In this study, in order to incorporate different criteria in the ranking procedure, we present to use data envelopment analysis (DEA) as a multi-criteria efficiency evaluation framework. One of the advantages of the DEA procedure is that it is able to determine the efficiency or inefficiency of each GMPE. Also, the DEA methodology is able to handle the situation in which several target intensity measures such as spectral amplitude in different structural periods are interested to be considered in the ranking procedure. In this study, the DEA procedure is applied to the Central Iran seismotectonic province. The results show that the DEA can well evaluate the efficiency of GMPEs, and can be used as supplements to existing ranking procedures.

中文翻译：

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基于数据包络分析的地震动预测方程选择和排序程序

摘要 概率地震危险性分析 (PSHA) 中的一个影响因素是选择合适的地震动预测方程 (GMPE)。为了处理认知不确定性的来源，最常见的方法是在逻辑树框架中考虑多个 GMPE。在这种方法中，选择的 GMPE 和为每个分配的权重通常由专家决定，主要是根据直觉。为了减少主观性在选择 GMPE 中的作用，近年来开发了一些基于拟合优度的统计标准。在本研究中，为了在排名过程中纳入不同的标准，我们提出使用数据包络分析 (DEA) 作为多标准效率评估框架。DEA 程序的优点之一是它能够确定每个 GMPE 的效率或低效率。此外，DEA 方法能够处理在排序过程中感兴趣的几个目标强度度量（例如不同结构时期的频谱幅度）的情况。在这项研究中，DEA 程序应用于伊朗中部地震构造省。结果表明，DEA 可以很好地评估 GMPEs 的效率，可以作为现有排序程序的补充。DEA 程序适用于伊朗中部地震构造省。结果表明，DEA 可以很好地评估 GMPEs 的效率，可以作为现有排序程序的补充。DEA 程序适用于伊朗中部地震构造省。结果表明，DEA 可以很好地评估 GMPEs 的效率，可以作为现有排序程序的补充。