Research on the modified surrogate model based on local RBF for concrete dam static and dynamic response analysis

Abstract

In recent years, as AI technology has advanced, online monitoring of dams has garnered increasing interest. In addition, surrogate model technology is a crucial component of online monitoring. As a result, developing a high-quality surrogate model has become one of the pillars of dam online monitoring. This work proposes a local radial basis function based on sensitivity modification to address the deficiencies of the current radial basis function. In addition, a benchmark function is utilized to validate the method’s viability. Comparisons with BP neural network and RBF demonstrate the usefulness of the proposed strategy. The analysis demonstrates that the proposed strategy for constructing a surrogate model of the dam’s structural behavior is possible and accurate. This paper aims to establish a high-quality surrogate model to provide technical support for dam online monitoring.