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| 水文模型参数优选的改进粒子群优化算法 | |
| 引用本文： | 张超,马金宝,冯杰.水文模型参数优选的改进粒子群优化算法[J].武汉大学学报(工学版),2011,44(2):182-186. |
| 作者姓名： | 张超 马金宝 冯杰 |
| 作者单位： | 1. 河海大学水文水资源与水利工程科学国家重点实验室,江苏,南京,210098 2. 山东省临沂市水利勘测设计院,山东,临沂,276000 3. 中国水利水电科学研究院水资源所,北京,100044 |
| 摘 要： | 针对标准粒子群算法的早熟收敛问题,提出了一个提高算法性能的改进途径,即引入动态改变惯性权重策略和混沌思想,在两个方面同时改进以提高粒子群算法的收敛速度和克服局部极值的能力.对两个函数进行寻优测试表明,改进后的粒子群算法收敛速度、精度以及全局搜索能力均优于标准粒子群算法.最后将提出的改进粒子群算法应用于新安江模型进行参数优选,应用结果表明,该算法具有较强的可行性与实用性. |
| 关 键 词： | 改进粒子群算法 动态改变惯性权重 混沌 新安江模型 参数优选 |
Improved particle swarm optimization algorithm for parameter optimization of hydrologic models |
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| ZHANG Chao,MA Jinbao,FENG Jie.Improved particle swarm optimization algorithm for parameter optimization of hydrologic models[J].Engineering Journal of Wuhan University,2011,44(2):182-186. | |
| Authors: | ZHANG Chao MA Jinbao FENG Jie |
| Affiliation: | ZHANG Chao1,MA Jinbao2,FENG Jie3(1.State Key Laboratory of Hydrology-Water Resources and Hydraulic Engineering,Hohai University,Nanjing 210098,China,2.Linyi Survey and Design Institute of Water Conservancy,Shandong Province,Lingyi 276000,3.Water ResourcesResearch Department,China Institute of Water Resources and Hydropower Research,Beijing 100044,China) |
| Abstract: | Aiming at the problem of premature convergence in the particle swarm optimization(PSO) algorithm,an improved algorithm is put forward.In the algorithm,the dynamic inertia weight is proposed and the chaos theory is introduced.By combining these two methods,the convergence rate of the algorithm and the capability of overcoming local extreme value are increased.Experiments on two functions show that the improved algorithm is prior to traditional PSO in convergence rate,precision and global searching ability.Th... |
| Keywords: | improved particle swarm optimization dynamic inertia weight chaos XAJ model parameter optimization |
| 本文献已被 CNKI 万方数据 等数据库收录！ | |
