A Method Based on PSO-RBF to the Optimization of Dam Structure
In hydraulic engineering fields, optimization is an important means to save investment and shorten construction time, however, traditional optimization methods based on gradient often confront with such problems as non-convergence or convergence to local optimum when it is applied in large-scale complicated hydraulic engineering problems. It is necessary to develop a new optimization method that possesses more ability to seek a global optimum. In this paper, a new method based on Particle Swarm Optimization (PSO) uniform design response surface and RBF neural network is introduced to optimize dam structure. The problem of convergence to local optimum can be solved efficiently; meanwhile, higher accuracy of optimization results can be acquired by this method in shorter time. An application example is presented to demonstrate the applicability of the proposed method.
Gravity dam Structural optimization PSO-RBF
Nannan Li Zhihong Qie Xinmiao Wu PanPan Gao
Agricultural University of Hebei, Baoding, 071001 China Agricultural University of Hebei, Baoding, 071001
国际会议
2011 China Control and Decision Conference(2011中国控制与决策会议 CCDC)
四川绵阳
英文
1846-1850
2011-05-23（万方平台首次上网日期，不代表论文的发表时间）