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首页> 外文期刊>Applied Soft Computing >Optimal design of arch dams subjected to earthquake loading by a combination of simultaneous perturbation stochastic approximation and particle swarm algorithms
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Optimal design of arch dams subjected to earthquake loading by a combination of simultaneous perturbation stochastic approximation and particle swarm algorithms

机译:组合摄动随机逼近与粒子群算法相结合的拱坝地震承载力优化设计。

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摘要

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 single methods is termed as SPSA-PSO. The operation of SPSA-PSO includes three phases. In the first phase, a preliminary optimization is accomplished using the SPSA. In the second phase, an optimal initial swarm is produced using the first phase results. In the last phase, the PSO is employed to find the optimum design using the optimal initial swarm. The numerical results demonstrate the high performance of the proposed strategy for optimal design of arch dams. The solutions obtained by the SPSA-PSO are compared with those of SPSA and PSO. It is revealed that the SPSA-PSO converges to a superior solution compared to the SPSA and PSO having a lower computation cost.
机译:引入了一种有效的优化程序,以考虑地震荷载作用下的流固耦合,找到拱坝的最佳形状。通过同时摄动随机逼近(SPSA)和粒子群优化(PSO)算法的组合来执行优化。这两种单一方法的串行集成称为SPSA-PSO。 SPSA-PSO的操作包括三个阶段。在第一阶段,使用SPSA完成初步优化。在第二阶段,使用第一阶段的结果生成最佳初始群。在最后阶段,使用PSO通过最佳初始群来找到最佳设计。数值结果证明了所提出策略对拱坝优化设计的高性能。将通过SPSA-PSO获得的解决方案与SPSA和PSO的解决方案进行比较。结果表明,与具有较低计算成本的SPSA和PSO相比,SPSA-PSO收敛到了一种更好的解决方案。

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