In actual concrete arch dam engineering scenarios, the dynamic data obtained by health monitoring system of an are incomplete. The acquired typically depend on state structure, that is, whether it is intact or Besides, future environmental loads structure unpredictable. Thus, noise also uncertain. practical engineering, use a damage identification model constructed based incomplete information ...

An efficient optimization procedure is introduced to find the optimal shapes of arch dams considering fluid–structure interaction subject to earthquake loading. The optimization is performed by a combination of simultaneous perturbation stochastic approximation (SPSA) and particle swarm optimization (PSO) algorithms. This serial integration of the two singlemethods is termed as SPSA–PSO. The op...

This study presents a least squares support vector machine (LSSVM) based displacement prediction model for health monitoring of concrete dams. LSSVM is a novel machine learning technique. The model can produce similar good generalization performance and learns faster than the basic support vector machines in engineering problems. The advantages such as high prediction accuracy, fast training sp...