| 大气污染预测中提高BP网络泛化能力的方法 |
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| 引用本文： | 秦侠,雷蕾,姚小丽.大气污染预测中提高BP网络泛化能力的方法[J].北京工业大学学报,2007,33(8):849-852. |
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| 作者姓名： | 秦侠 雷蕾 姚小丽 |
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| 作者单位： | 北京工业大学,环境与能源工程学院,北京,100022;北京工业大学,环境与能源工程学院,北京,100022;北京工业大学,环境与能源工程学院,北京,100022 |
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| 摘 要： | 为了通过预测大气环境的质量和发展变化,来寻求有效地控制和改善环境质量的相应措施,选用英国伦敦马里波恩监测站PM_(2.5)的小时平均浓度监测资料,采用贝叶斯归一化训练算法和提前终止法泛化改进的BP神经网络模型,预报PM_(2.5)的24 h内的各小时浓度.结果表明,采用本方法进行空气污染预报,预测相对误差为20%～49%,提高了预报网络的泛化能力.
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| 关 键 词： | BP网络 泛化能力 PM2.5 污染预测 |
| 文章编号： | 0254-0037（2007）08-0849-03 |
| 修稿时间： | 2006-08-24 |
Methods to Improve the Generalization of BP Neural Network Applied in Air Pollution Forecasting |
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| QIN Xia,LEI Lei,YAO Xiao-li.Methods to Improve the Generalization of BP Neural Network Applied in Air Pollution Forecasting[J].Journal of Beijing Polytechnic University,2007,33(8):849-852. |
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| Authors: | QIN Xia LEI Lei YAO Xiao-li |
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| Affiliation: | College of Environmental and Energy Engineering;Beijing University of Technology;Beijing 100022;China |
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| Abstract: | Atmospheric pollution prediction is helpful to find effective ways to control air pollution and improve air quality.BP neural network which was trained using Bayesian Regularization method and early stopping method was used to forecast the hourly concentration of PM_(2.5).The data of PM_(2.5) hourly concentration were obtained from monitoring site of Marylebone Road in London,UK.The prediction relative error goes from 20% to 49%.The results show that compared with networks which were trained using other met... |
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| Keywords: | back propagation network generalisation PM2 5 pollution prediction |
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