Prediction of long-term temperature effect in structural health monitoring of concrete dams using support vector machines with Jaya optimizer and salp swarm algorithms.
【作者单位】1 School of Hydraulic Engineering, Faculty of Infrastructure Engineering, Dalian University of Technology, Dalian 116024, PR China 2 School of Engineering, Tibet University, Lhasa 850012, PR China 3 State Grid XinYuan Company Ltd. Maintenance Branch, Beijing 100068, PR China
【年份】2019
【卷号】Vol.131
【页码】60-76
【ISSN】0965-9978
【关键词】support vector machines Concrete gravity dams Jaya optimization Long term air temperature effect Salp swarm algorithms Structural health monitoring
【摘要】 Highlights • Dam behavior prediction algorithms are essential for safety monitoring of large dams. • Novel parameter-free multi-population based Jaya-SVM (or LSSVM) and SSA-SVM models were proposed for modeling of the behavior of concrete dams. • Jay...
