| 基于粒子群优化算法的BP网络模型在径流预测中的应用 |
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| 引用本文： | 杨道辉,马光文,刘起方,陶春华,过夏明.基于粒子群优化算法的BP网络模型在径流预测中的应用[J].水力发电学报,2006,25(2):65-68. |
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| 作者姓名： | 杨道辉 马光文 刘起方 陶春华 过夏明 |
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| 作者单位： | 四川大学水电学院,成都,610065 |
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| 基金项目： | 国家高技术研究发展计划(863计划) |
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| 摘 要： | 本文介绍了一种全局随机优化算法一粒子群优化算法,并将其用于BP网络模型,对模型参数进行优化来提高模型的收敛速度和精度。最后利用参数优化前后的BP模型进行径流预测,结果表明模型收敛速度和精度明显提高。
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| 关 键 词： | 水资源 径流预测 粒子群算法 人工神经网络 |
| 收稿时间： | 2004-12-27 |
| 修稿时间： | 2004年12月27 |
Runoff prediction by BP networks model based on PSO |
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| YANG Daohui,MA Guangwen,LIU Qifang,TAO Chunhua,GUO Xiaming.Runoff prediction by BP networks model based on PSO[J].Journal of Hydroelectric Engineering,2006,25(2):65-68. |
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| Authors: | YANG Daohui MA Guangwen LIU Qifang TAO Chunhua GUO Xiaming |
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| Affiliation: | School of Hydropower Engineering, Sichuan University, Chengdu 610065 |
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| Abstract: | Particle swarm optimizer(PSO) algorithm with the global stochastic optimization technique is introduced and applied to BP neural networks to optimize the parameters of BP neural networks so as to improve the convergence speed and precision of BP neural networks.The runoff predicting results are obtained from two different kinds of BP neural networks,it is shown that convergence speed and precision of BP neural networks are improved. |
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| Keywords: | water resource runoff predicting particle swarm optimizer(PSO) ANN |
| 本文献已被 CNKI 维普 万方数据 等数据库收录！ |
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