| 刘苏宁,甘泓,魏国孝.粒子群算法在新安江模型参数率定中的应用[J].水利学报,2010,41(5): |
| 粒子群算法在新安江模型参数率定中的应用 |
| Application of PSO algorithm to calibrate the Xin’anjiang Hydrological Model |
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| DOI： |
| 中文关键词: 径流模拟 新安江水文模型 PSO 算法 算法性能分析 参数选择 |
| 英文关键词: water consumption water budget evapotranspiration energy balance SEBAL model MODIS satellite data Sanjiang Plain |
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| 中文摘要: |
| 选用1997 年中国水文预报竞赛中降雨、蒸发、径流数据，重点研究在应用粒子群优化算法( PSO) 率定新安江模型参数时，PSO 算法中惯性权重、加速度常数和种群规模3 个参数对算法性能的影响，并优选出适合于该问题的最优PSO 参数区间。在此基础上率定出与研究流域匹配的新安江模型参数，定量评价了降雨径流模拟效果的优劣。另外，对PSO 算法的效率和稳定性进行了简要分析。研究结果表明，PSO 算法率定新安江模型参数的收敛效率较传统方法明显提高，稳定性普遍较好。 |
| 英文摘要: |
| Based on the hydrological data sets used in China Hydrology Forecasting Test 1997，the influences of inertia weights，acceleration constant and swarm size on the performance of Particle Swarm Optimization algorithm in calibrating the Xin’anjiang Model was analyzed，and a group of optimal intervals was chosen. Then，a set of optimal Xin’anjiang Hydrological Model parameters were selected. Its efficiency in rainfall-runoff forecasting was also analyzed quantitatively. Additionally，the efficiency of POS algorithm was investigated. The stability analysis of POS algorithm was also carried out. The study result shows that the calibration efficiency of parameters of Xin’anjiang Model by using PSO algorithm is much higher than that of traditional method，and the stability is good. |
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