| 应用人工神经网与遗传算法进行短期负荷预测 |
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| 引用本文： | 岑文辉,雷友坤,谢,恒.应用人工神经网与遗传算法进行短期负荷预测[J].电力系统自动化,1997,21(3):29-32. |
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| 作者姓名： | 岑文辉 雷友坤 谢 恒 |
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| 作者单位： | 上海交通大学电力工程系 |
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| 摘 要： | 针对ＢＰ网络的缺陷，提出了基于拟牛顿法的自适应算法和改进的遗传算法，以提高神经网的学习效率，克服ＢＰ网络的局部收敛性的缺点，形成一种新的神经网与遗传算法相结合的短期负荷预测模型，实测结果表明该模型和算法具有良好的性能和较高的预测精度。
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| 关 键 词： | 人工神经网 遗传算法 负荷预测 电力系统 |
| 收稿时间： | 1/1/1900 12:00:00 AM |
| 修稿时间： | 1/1/1900 12:00:00 AM |
SHORT TERM LOAD FORECASTING WITH ARTIFICIAL NEURAL NETWORK AND GENETIC ALGORITHMS |
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| Chen Wenhui,Lei Youkun,Xie Heng.SHORT TERM LOAD FORECASTING WITH ARTIFICIAL NEURAL NETWORK AND GENETIC ALGORITHMS[J].Automation of Electric Power Systems,1997,21(3):29-32. |
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| Authors: | Chen Wenhui Lei Youkun Xie Heng |
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| Abstract: | This paper presents a new hybrid artificial neural network (ANN) learning algorithm, which combines the adapted learning algorithm based on quasi Newton method and the improved genetic algorithms (GA) It possesses merits of high speed of convergence and higher precision A new hybrid short term load forecasting model is built with the above algorithms Satisfactory results are obtained by applying it to a certain network |
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| Keywords: | artificial neural network (ANN) genetic algorithm (GA) short term load forecasting the adapted learning algorithm based on quasi Newton method |
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