摘要
文中结合水库2000-2010年实测水文数据进行对比分析,应用粒子群优化算法和遗传算法对新安江模型的参数进行优化分析。结果表明:粒子群优化算法高于遗传算法的参数优化程度。粒子群优化算法的优化参数值水库水文模拟的精度明显高于遗传算法的模拟精度,且粒子群优化算法的收敛精度更高。
Combined with the comparative analysis of observed hydrological data from 2000 to 2010 for a reservoir,the paper optimizes and analyzes the parameters of Xin'anjiang model by using the particle swarm optimization al gorithm and the genetic algorithm. The results show that the particle swarm optimization algorithm has higher optimization degree than the genetic algorithm. For the hydrological simulation of the reservoir, the precision of the particle swarm optimization algorithm by optimized parameters has obviously higher than the genetic algorithm and has the higher convergence precision.
出处
《东北水利水电》
2016年第6期48-51,5,共4页
Water Resources & Hydropower of Northeast China
关键词
参数
优化算法
遗传算法
新安江模型
parameter
optimization algorithm
genetic algorithm
Xin'anjiang model
