公开(公告)号：US12197831B1

公开(公告)日：2025-01-14

申请号：US18739249

申请日：2024-06-10

Applicant: Southeast University

Inventor： Decheng Feng ,  Jiayi Ding ,  Xuyang Cao ,  Shizhi Chen ,  Gang Wu

IPC: G06F30/27

Abstract: The invention discloses a ground motion intensity measure optimization method for seismic response prediction. The method includes the following steps: (1) building a building damage database; (2) optimizing ground motion intensity measures; (3) constructing a machine learning model; and (4) predicting damage states. According to the method, a combination of optimal ground motion intensity measures is selected by an elastic-net algorithm, wherein the efficiency and practicability in a current selection criterion are updated based on the goodness of fit and regression coefficient of the elastic-net model, thereby avoiding an assumption that intensity measures and structure response need to obey a logarithmic linear relationship and the limitation of intensity measure dimensions in traditional methods. By using the combination of optimal ground motion intensity measures as input variables, the prediction accuracy can be remarkably improved, and meanwhile the number of samples required is reduced.