| 基于免疫小波网络的短期负荷预测模型 |
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| 引用本文： | 吴宏晓,侯志俭.基于免疫小波网络的短期负荷预测模型[J].电力系统及其自动化学报,2005,17(6):31-34. |
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| 作者姓名： | 吴宏晓 侯志俭 |
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| 作者单位： | 上海交通大学电子信息与电气工程学院,上海,200030 |
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| 摘 要： | 为了克服传统BP神经网络在结构设计和学习算法中存在的缺陷,提出了一种免疫小波网络(IWN)来预测电力系统短期负荷.在IWN的设计中,根据共生进化和免疫规划原理,提出共生进化免疫规划算法,可以自动确定小波网络隐层神经元的数量和参数.电力系统短期负荷预测的算例计算表明,与传统的BP神经网络预测方法相比,该方法具有更高的预测精度.
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| 关 键 词： | 免疫小波网络 短期负荷预测 免疫规划 |
| 文章编号： | 1003-8930（2005）06-0031-04 |
| 收稿时间： | 2005-01-14 |
| 修稿时间： | 2005-03-28 |
Short-Term Load Forecasting Using Immune Wavelet Network |
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| WU Hong-xiao,HOU Zhi-jian.Short-Term Load Forecasting Using Immune Wavelet Network[J].Proceedings of the CSU-EPSA,2005,17(6):31-34. |
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| Authors: | WU Hong-xiao HOU Zhi-jian |
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| Affiliation: | School of Electric Information and Electrical Engineering, Shanghai Jiaotong University, Shanghai 200030, China |
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| Abstract: | The IWN is presented to overcome the weakness of BP neural network(BPNN) for short-term load forecasting.In the design of the IWN,a novel algorithm based on the symbiotic evolutionary and the immune programming method(SEIPM) is proposed. The SEIPM can automatically adjust the number and parameters of hidden neurons. The proposed IWN model has been implemented using actual data and compared with the traditional BPNN method.The forecasting results demonstrate that the IWN method possesses superior forecast precision than the BPNN method does. |
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| Keywords: | immune wavelet network(IWN) short-term load forecasting immune programming |
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