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论文类型：期刊论文

发表时间：2019-10-01

发表刊物：ARABIAN JOURNAL FOR SCIENCE AND ENGINEERING

收录刊物：SCIE

卷号：44

期号：10

页面范围：8661-8673

ISSN号：2193-567X

关键字：Structural health monitoring; Temperature; MARS; Concrete gravity dams; Multiple linear regression

摘要：This paper presents a dam health monitoring model using long-term air temperature based on multivariate adaptive regression splines (MARS). MARS is an intelligent machine learning technique that has been successfully applied to deal with nonlinear function approximation and complex regression problems. The proposed long-term air temperature-based dam health monitoring model was verified on a real concrete gravity dam with efficient safety monitoring data. Results show that the proposed approach is promising for concrete dam behavior modeling considering the prediction error is much reduced.