| 基于径向基网络的燃气短期负荷预测 |
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| 引用本文： | 谭洪艳,刘延智,白金锋.基于径向基网络的燃气短期负荷预测[J].冶金能源,2006,25(5):14-16. |
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| 作者姓名： | 谭洪艳 刘延智 白金锋 |
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| 作者单位： | 1. 鞍山科技大学,114044,辽宁省鞍山市
2. 鞍山市煤气总公司 |
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| 摘 要： | 用径向基（RBF）神经网络对城市燃气系统进行短期负荷预测。在对鞍山市燃气系统的历史负荷数据进行短期预测结果表明，所建立的RBF神经网络模型具有较高的预测精度。
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| 关 键 词： | 城市燃气 人工神经网络 短期负荷预测 径向基函数 |
| 收稿时间： | 05 8 2006 12:00AM |
| 修稿时间： | 2006-05-08 |
Short-term gas load forecasting based on RBF neural network |
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| Tan Hongyan,Liu Yanzhi,Bai Jinfeng.Short-term gas load forecasting based on RBF neural network[J].Energy For Metallurgical Industry,2006,25(5):14-16. |
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| Authors: | Tan Hongyan Liu Yanzhi Bai Jinfeng |
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| Affiliation: | Tan Hongyan Bai Jinfeng(Anshan University of Science and Technology) Liu Yanzhi(Anshan Gas Parent Company) |
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| Abstract: | The radial basis function neural network(RBF)is used in shortterm gas load forecasting in city gas system.The result has shown that the model is accurate when short-term gas load is forecasted with historical data of Anshan gas system. |
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| Keywords: | city gas artificial neural network short- term load forecasting radial basis function |
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