| 基于遗传算法的BP网络在黄河三门峡年径流量预测中的应用 |
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| 引用本文： | 陶海龙,黄卫东,颜帮琼,张胜召,刘阳彬.基于遗传算法的BP网络在黄河三门峡年径流量预测中的应用[J].水文,2012,32(3):34-37. |
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| 作者姓名： | 陶海龙 黄卫东 颜帮琼 张胜召 刘阳彬 |
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| 作者单位： | 1. 兰州交通大学机电技术研究所,甘肃兰州,730070
2. 中国水利水电第五工程局有限公司,四川成都,610066 |
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| 摘 要： | 提出了一种基于遗传算法(genetic algorithms,GA)的BP神经网络模型来进行径流量预测。此模型融合了遗传优化算法的全局寻优能力和BP神经网络的局部搜索的优势,有效地防止了网络陷入局部极小值,同时又保证了预测结果的精确性。仿真实验结果表明:在黄河三门峡1950~1985年年径流量预测方面,GA-BP模型预测的平均相对误差为5.67%,标准BP算法的模型平均预测误差为11.05%,说明提出的GA-BP径流量方法行之有效。
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| 关 键 词： | 遗传算法 BP神经网络 年径流量 预测 三门峡 |
Application of GA-based BP Network in Annual Runoff Predication at Sanmenxia of Yellow River |
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| TAO Hailong
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HUANG Weidong
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YAN Bangqiong
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ZHANG Shenzhao
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LIU Yangbin.Application of GA-based BP Network in Annual Runoff Predication at Sanmenxia of Yellow River[J].Hydrology,2012,32(3):34-37. |
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| Authors: | TAO Hailong HUANG Weidong YAN Bangqiong ZHANG Shenzhao LIU Yangbin |
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| Institution: | 1.Mechatronieal T8LR Institute,Lanzhou Jiaotong University,Lanzhou 730070,China; 2.Sinohydro Bureau 5 Co.ltd,Chengdu 610066,China) |
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| Abstract: | A GA-based BP network model was presented and applied to runoff prediction at Sanmenxia of the Yellow River.The model combined with GA for global optimization ability and BP neural network advantages of local search,to effectively prevent the network fall into a local minimum,at the same time guarantee the accuracy of prediction results.The simulation results show that,as for the annual runoff at Sanmenxia of the Yellow River from 1950 to 1985,the average relative error of GA-BP prediction model is 5.76%,but the average relative error of standard BP network prediction model is 11.05%,indicating that GA-BP prediction method is effective and feasible. |
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| Keywords: | GA BP neural network annual runoff prediction Sanmenxia |
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