| 中长期电力负荷预测 |
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| 引用本文： | 纪官燚. 中长期电力负荷预测[J]. 潍坊学院学报, 2004, 4(4): 98-99 |
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| 作者姓名： | 纪官燚 |
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| 作者单位： | 潍坊学院,计算机科学系,山东,潍坊,261061 |
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| 摘 要： | 对电力负荷的预测的传统方法主要采用回归模型、曲线模型等，因不能充分利用历史数据，其准确性较差。利用人工智能技术，将BP神经网络及遗传算法应用于中长期期电力负荷预测，能更好的利用历史数据，如果再对有节假日的特殊月季电力负荷数据进行合理有效的处理，就能大大提高预测的精度。
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| 关 键 词： | 电力负荷 预测方法 人工智能 神经网络 遗传算法 |
| 文章编号： | 1671-4288(2004)04-0098-02 |
| 修稿时间： | 2003-04-26 |
Middle or Long-term Electric Power Carry Predicting |
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| JI Guan-yi. Middle or Long-term Electric Power Carry Predicting[J]. Journal of Weifang University, 2004, 4(4): 98-99 |
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| Authors: | JI Guan-yi |
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| Abstract: | Traditional methods of predicting electric power carry including the return model and the curve model etc., its accuracy is bad because of not using the historical data. Validity is high to make full use of the historical data with the artificial intelligence technique, BP nerve network and GA-in nuddle or long-term electric power carry predicting, if righdy and validly handling the electric power carry data of festivals ,it will greatly increase the estimate' s accuracy. |
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| Keywords: | electric power cany predicting BP nerve network GA multi-cross factor compare-value model |
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