| 基于人工鱼群算法神经网络的电力系统短期负荷预测 |
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| 引用本文： | 刘耀年,庞松岭,刘岱.基于人工鱼群算法神经网络的电力系统短期负荷预测[J].电工电能新技术,2005,24(4):5-8. |
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| 作者姓名： | 刘耀年 庞松岭 刘岱 |
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| 作者单位： | 东北电力学院,吉林省,吉林市,132012 |
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| 摘 要： | 人工鱼群算法是一种新型的寻优策略,文中将人工鱼群算法用于RBF神经网络的训练过程,建立了相应的优化模型.依据人工鱼群算法的神经网络,提出一种短期负荷预测的新方法,实践表明:该方法具有预测精度高、误差小的优点,是值得广泛推广的好方法.
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| 关 键 词： | 人工鱼群算法 RBF神经网络 短期负荷预测 |
| 文章编号： | 1003-3076（2005）04-0005-04 |
| 收稿时间： | 2005-06-17 |
| 修稿时间： | 2005年6月17日 |
Short-term load forecasting method based on artificial fish-swarm algorithm of neural network |
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| LIU Yao-nian,PANG Song-ling,LIU Dai.Short-term load forecasting method based on artificial fish-swarm algorithm of neural network[J].Advanced Technology of Electrical Engineering and Energy,2005,24(4):5-8. |
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| Authors: | LIU Yao-nian PANG Song-ling LIU Dai |
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| Affiliation: | Northeast China Institute of Electric Power Engineering, Jilin 132012, China |
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| Abstract: | Artificial fish-swarm algorithm (AFSA) is a nove1 optimizing method proposed lately. An Artificial Fish-swarm Algorithm for the RBF neural networks and a model based on this method were presented of the first time here. A short-term load forecasting technique for power system based on artificial fish-swarm algorithm of neural network is presented. Theoretical analysis and computer simulation results demonstrate that the forecasting method has the advantage of higher forecasting accuracy and smaller forecasting error. The method should be popularized. |
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| Keywords: | artificial fish-swarm algorithm RBF neural networks short-term load forecasting |
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