期刊文献+

人工神经网络与遗传算法在河道洪水预报中的应用 被引量:5

Research on Flood Forecasting Method of Rivers Based on Artificial Neural Networks and Genetic Algorithms
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摘要 在总结大量洪水智能预报实践经验的基础上,主要作了两方面的工作:(1)提出了一种能够进行峰值识别的改进BP算法(ErrorBackPropagationwithPeakRecognizer,简称BPPR),该算法在修改网络权重时偏重大值,即大值误差对权重的修改起主要作用,从而提高模型对洪峰峰值的预报精度.(2)采用遗传算法优化网络的初始权重,以解决BP网络训练容易落入局部极小点的问题.
出处 《水利发展研究》 2002年第12期50-55,58,共7页 Water Resources Development Research
基金 国家自然科学基金资助项目(59809007).
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  • 2王春平,王金生,梁团豪.人工智能在洪水预报中的应用[J].水力发电,2005,31(9):12-15. 被引量:11
  • 3王晓玲,李松敏,段文泉,孙月峰.基于隶属度-遗传神经网络模型的水质综合评价[J].天津大学学报,2006,39(10):1199-1204. 被引量:11
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共引文献48

同被引文献39

  • 1于文莉,陈亚军,周伟忠,于文华.基于遗传算法和BP神经网络的优化设计方法[J].湖州师范学院学报,2004,26(2):56-58. 被引量:5
  • 2王春平,王金生,梁团豪.人工智能在洪水预报中的应用[J].水力发电,2005,31(9):12-15. 被引量:11
  • 3王晓玲,李松敏,段文泉,孙月峰.基于隶属度-遗传神经网络模型的水质综合评价[J].天津大学学报,2006,39(10):1199-1204. 被引量:11
  • 4Cater L W. Environment Impact Assessment [M]. 2nd ed.Singapore: McGraw-Hill Inc, 1996.
  • 5Wang Haiyan. Assessment and prediction of overall environmental quality of Zhuzhou City, Hunan Province, China[J]. Journal of Environmental Management, 2002,66(3):329-340.
  • 6Yang Tao,Yang Xinmiao. Fuzzy comprehensive assessment,fuzzy clustering analysis and its application for urban traffic environment quality evaluation [J]. Transportation Research-D,1998,3(1):51-57.
  • 7Zhang Yuanzhi, Pulliainen Jouni, Koponen Sampsa, et al.Application of an empirical neural network to surface water quality estimation in the Gulf of Finland using combined optical data and microwave data [J]. Remote Sensing of Environment ,2002,81 (2):327-336.
  • 8Yuan Ximin, Li Hongyan. Raising flood forecasting precision based on improving artificial neural networks algorithm[M].XXIX IAHR Congress Proceedings. Theme C, Beijing:Tsinghua University Press,2001.
  • 9Wen Xiulan, Song Aiguo. Evolving neural networks using an improved genetic algorithm [J]. Journal of Southeast University,2002,18(4):367-369.
  • 10Fernando DAK, Jayawardena AW. Runoff forecasting using RBF networks with OLS algorithm [ J ]. J Hydrologic Engrg, ASCE, 1998,3 ( 3 ) : 203 - 209.

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