| 改进灰色神经网络模型在电量预测中的应用 |
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| 引用本文： | 万星,周建中.改进灰色神经网络模型在电量预测中的应用[J].水力发电,2007,33(6):69-72,88. |
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| 作者姓名： | 万星 周建中 |
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| 作者单位： | 1. 华中科技大学,湖北,武汉,430074;重庆交通大学,重庆,400074
2. 华中科技大学,湖北,武汉,430074 |
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| 摘 要： | 研究过程中分析比较了人工神经网络和灰色模型的优缺点,尝试将人工神经网络模型与改进灰色模型进行有机结合,从而提出了改进灰色神经网络模型。新的耦合方式发挥了灰色预测方法中累加生成的优点,便于神经网络进行训练,又避免了灰色预测方法带来的误差,提高了预测精度,是一种新的有益探索;为实际工程应用提供了重要的参考。
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| 关 键 词： | 改进灰色 神经网络 电力负荷 预测评价 |
| 文章编号： | 0559-9342（2007）06-0069-04 |
| 修稿时间： | 2006-12-13 |
Application Of Improved Grey Neural Networks Model In Electricity Load Forecast |
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| Wan Xing,Zhou Jianzhong.Application Of Improved Grey Neural Networks Model In Electricity Load Forecast[J].Water Power,2007,33(6):69-72,88. |
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| Authors: | Wan Xing Zhou Jianzhong |
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| Affiliation: | 1.Huazhong University of Science and Technology, Wuhan Hubei 430074; 2.Chong Qing Jiaotong University, Chongqing 400074 |
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| Abstract: | In the research process, this paper has analyzed and compared the advantages and disadvantages of manual ANN and improved grey model, tried to combined manual ANN with improved grey model organically, and put forward improved grey ANN model. New coupling method has exerted the advantages accumulated and formed in grey forecast method, not only easy to ANN training, but also avoid error caused by grey forecast method. Thus is a sort of new and available study for improving forecast precision, which provides important reference value in actual construction application. |
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| Keywords: | improved grey model neural networks electric load prognosis and assessment |
| 本文献已被 CNKI 维普 万方数据 等数据库收录！ |
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