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基于粒子群神经网络的凌汛开河日期预测研究
引用本文:赵晓慎,吴海波,王文川,李倩. 基于粒子群神经网络的凌汛开河日期预测研究[J]. 人民长江, 2011, 42(19): 77-79
作者姓名:赵晓慎  吴海波  王文川  李倩
作者单位:华北水利水电学院水利学院,河南郑州,450011
基金项目:河南省教育厅自然科学研究计划项目(2010B570002); 华北水利水电学院高层次人才科研启动资助项目(200821)
摘    要:为了更准确地预测凌汛开河日期,提出用粒子群算法和BP神经网络相结合的粒子群神经网络模型。介绍了模型的设计和算法实现的流程。该模型通过粒子群算法对BP神经网络初始的权值和阈值进行优化,并以黄河内蒙段三湖河口站作为研究实例进行冰凌开河日期预测。结果表明,经粒子群优化后的BP神经网络预测精度比遗传神经网络和单一BP神经网络更高。

关 键 词:凌汛  开河日期  粒子群优化算法  BP神经网络  遗传算法  

Prediction of beginning date of ice jam flood based on particle swarm optimization-neural network model
ZHAO Xiaoshen,WU Haibo,WANG Wenchuan,LI Qian. Prediction of beginning date of ice jam flood based on particle swarm optimization-neural network model[J]. Yangtze River, 2011, 42(19): 77-79
Authors:ZHAO Xiaoshen  WU Haibo  WANG Wenchuan  LI Qian
Affiliation:ZHAO Xiaoshen,WU Haibo,WANG Wenchuan,LI Qian(College of Water Conservancy,North China University of Water Resources and Electric Power,Zhengzhou 450011,China)
Abstract:In order to predict the beginning date of ice jam flood more accurately,the particle swarm optimization-neural network model is proposed by the combination of particle swarm optimization algorithm and BP neural network.The design of the model and flow of the algorithm realization is presented.The initial weights and thresholds of BP network are optimized by using particle swarm optimization algorithm,and taking the Sanhuhekou Station of Yellow River in the Inner Mongolia as example,the beginning date of ice...
Keywords:ice jam flood  beginning date  particle swarm optimization algorithm  BP neural network  genetic algorithm  
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