| 改进遗传神经网络及其在负荷预测中的应用 |
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| 引用本文： | 高海龙,张国立.改进遗传神经网络及其在负荷预测中的应用[J].华北电力大学学报,2009,36(5). |
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| 作者姓名： | 高海龙 张国立 |
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| 作者单位： | 1. 华北电力大学计算机科学与技术学院,河北,保定,071003
2. 华北电力大学数理学院,河北,保定,071003 |
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| 基金项目： | 华北电力大学留学归国人员基金资助项目 |
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| 摘 要： | 针对遗传算法早熟的缺陷,提出了改进的交叉,变异策略,采用移民算子等方法改善遗传算法的性能,并把此方法应用到神经网络的训练中,对电力系统短期负荷进行预测取得了较为理想的效果。
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| 关 键 词： | 遗传算法 神经网络 负荷预测 |
Improved genetic neural network and its application in load forecasting |
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| Abstract: | According to the premature shortcoming of GA,a well designed crossover and mutation strategy were proposed and the implementation were presented in detail,and the immigrate operator was adopted to improve the performance of GA.Finally,the method was applied to the training of ANN,and a well result in short-term load forecasting was achieved. |
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| Keywords: | genetic algorithm neural networks power load forecasting |
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