| BP神经网络模型结构对漫湾径流预报精度的影响研究 |
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| 引用本文： | 程春田,孙英广,林剑艺.BP神经网络模型结构对漫湾径流预报精度的影响研究[J].水电能源科学,2005,23(2):4-6. |
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| 作者姓名： | 程春田 孙英广 林剑艺 |
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| 作者单位： | 大连理工大学,土木水利学院,辽宁,大连,116024 |
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| 基金项目： | 国家自然科学基金资助项目(50479055) |
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| 摘 要： | 以云南省漫湾水电站历史径流状况为研究对象，运用三层前馈反向传播神经网络模型对径流进行中长期预报。为解决神经网络预报模型结构难以确定的问题，尝试在预报过程中通过改变该网络模型的结构并对得到的结果进行比较，从而找到适合该径流序列的最佳神经网络模型结构。实际应用表明，使用该结构的模型在实际预报过程中取得了良好的效果。
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| 关 键 词： | 径流中长期预报 人工神经网络 前馈反向传播模型 |
| 文章编号： | 1000-7709(2005)02-0004-03 |
| 修稿时间： | 2004年12月14 |
Analysis of Effects of BP Artificial Neural Network Structures on Precision of Flow Forecasting for Manwan Reservoir |
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| CHENG Chuntian.Analysis of Effects of BP Artificial Neural Network Structures on Precision of Flow Forecasting for Manwan Reservoir[J].International Journal Hydroelectric Energy,2005,23(2):4-6. |
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| Authors: | CHENG Chuntian |
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| Abstract: | A three-tiered artificial neural network (ANN) model with a feed-forward, back-propagation network structure was developed to forecast river flow in the Manwan Reservoir. Based on historical data, various ANN models with different structure were analyzed and tested in order to find a satisfied one. The results of application have showed that the used ANN model is successful and effective in the hydrologic forecasting of the Manwan Reservoir. |
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| Keywords: | medium and long-term flow forecasting ANN feed-forward back-propagation network |
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