| 基于Matlab的BP-NN时间序列法预测地表水资源量 |
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| 引用本文： | 赵显波,雷晓云,刘振平.基于Matlab的BP-NN时间序列法预测地表水资源量[J].水文,2007,27(2):34-36. |
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| 作者姓名： | 赵显波 雷晓云 刘振平 |
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| 作者单位： | 新疆农业大学,水利与土木工程学院,新疆,乌鲁木齐,830052 |
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| 摘 要： | 本文以Matlab神经网络工具箱GUI为依托,用地表水资源时间序列的年径流量资料作为训练样本的基础,生成训练样本输入数据和期望输出数据,建立时间序列神经网络预测模型。模型优点可以模拟多变量而不需要对输入变量作复杂的关系假定,不要求知道输入输出变量之间的关系,只需通过用误差反向传播的(BP)算法训练神经网络,获得输入输出之间的映射关系。最后,以玛纳斯河肯斯瓦特站历年的年径流资料验证时间序列人工神经网络预测模型的可行性与有效性。
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| 关 键 词： | BP神经网络 时间序列 预测 |
| 文章编号： | 1000-0852（2007）02-0034-03 |
| 修稿时间： | 2006-06-07 |
Surface Water Quantity Forecasting with Time Series Method of BP-NN Based on Matlab |
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| ZHAO Xian-bo,LEI Xiao-yun,LIU Zhen-ping.Surface Water Quantity Forecasting with Time Series Method of BP-NN Based on Matlab[J].Hydrology,2007,27(2):34-36. |
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| Authors: | ZHAO Xian-bo LEI Xiao-yun LIU Zhen-ping |
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| Institution: | College of Water Conservancy and Civil Engineering, Xinjiang Agricultural University, Urumuqi 830052, China |
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| Abstract: | This paper created train sample input and expectation output data relying on Neural Networks tool boxes GUI based on Matlab with surface water resource quantity time series data as train sample basic,then make forecasts based a model of temporal serial Neural Network.The merits of the model is that it can simulate numerous variable and obtain mapped connection between them by train Back Propagation Neural Networks without needing to assume intricate connection input variable,and without needing to know connection between input and output variable.Lastly,the feasibility and validity of the model was validated with the past years surface water resource quantity time series data from Kenswat Station on Xinjiang Manas River. |
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| Keywords: | Matlab |
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