文献类型：期刊文献

中文题名：基于ABC-BP神经网络的洪水预测研究

英文题名：Research on Flood Prediction Base on The ABC-BP Neural Network

作者：马玉磊[1];赵芳[2]

第一作者：马玉磊

机构：[1]新乡学院继续教育学院;[2]新乡学院计算机与信息工程学院

第一机构：新乡学院

年份：2014

卷号：0

期号：1

起止页码：41-46

中文期刊名：西南师范大学学报：自然科学版

收录：CSTPCD;;北大核心:【北大核心2011】；CSCD:【CSCD_E2013_2014】；

基金：河南省科技计划发展项目资助(112300410266)

语种：中文

中文关键词：人工蜂群算法;BP神经网络;洪水预测;径流量

外文关键词：artificial bee colony algorithm;;the BP neural network;;flood prediction;;runof

摘要：该文介绍了人工蜂群算法(ABC)和BP神经网络算法,详细阐述ABC算法优化BP神经网络的权值和阈值.通过实验仿真对比,该文提出的算法预测结果比仅仅使用BP神经网络算法以及混沌径向基神经网络模型算法精度更高,是一种有效可靠的洪水预测方法.
The flood prediction model has been proposed on the basis of artificial bee colony algorithm (ABC)optimizes BP neurotic network algorithm.With BP neural network as the foundation,extract ob-servation stations in previous years,the average runoff as flood properties.By means of ABC-BP neural network algorithm to optimize the various parameters,the model has finally been established,and the flood forecasting model of the watershed stations put into use.This article describes the ABC algorithm and BP neural network algorithm,which is elaborated on the ABC algorithm to optimize BP neural net-work weights and threshold.Through the comparison of the experimental simulation,forecasting results have been obtained by this method than BP neural network algorithm with the higher accuracy,and it is an effective and reliable method.