| 基于灰色支持向量机组合模型的我国火电NOx排放量预测 |
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| 引用本文： | 赵 毅,周建国,梁怀涛. 基于灰色支持向量机组合模型的我国火电NOx排放量预测[J]. 环境科学研究, 2011, 24(5): 489-496 |
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| 作者姓名： | 赵 毅 周建国 梁怀涛 |
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| 作者单位： | 1.华北电力大学环境科学与工程学院, 河北 保定 071003 |
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| 摘 要： | 区域火电NOx排放量的预测属于小样本、贫信息的灰色系统. 由于NOx排放量受多个因素的叠加性影响，单一预测模型难以准确反映NOx排放量的复杂变化，易产生较大的预测误差. 基于此，利用灰色预测理论和支持向量机预测理论，建立了火电NOx排放量组合优化预测模型. 采用国家权威部门发布的火电NOx排放量数据，综合考虑影响我国火电NOx排放量的主要因素，对我国2008—2010年以及2020年的火电NOx排放量进行了预测，预测结果与官方公布的实际值基本一致; 同时，预测的时间大大缩短.
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| 关 键 词： | NOx排放量 灰色预测模型 支持向量机 组合预测模型 |
| 收稿时间： | 2010-11-10 |
| 修稿时间： | 2011-01-08 |
Prediction of NOx Emissions from Thermal Power Plants in China Based on a Grey Support Vector Machine Combination Model |
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| ZHAO Yi,ZHOU Jian-guo and LIANG Huai-tao. Prediction of NOx Emissions from Thermal Power Plants in China Based on a Grey Support Vector Machine Combination Model[J]. Research of Environmental Sciences, 2011, 24(5): 489-496 |
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| Authors: | ZHAO Yi ZHOU Jian-guo LIANG Huai-tao |
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| Affiliation: | 1.College of Environmental Science and Engineering, North China Electric Power University, Baoding 071003, China2.College of Economics and Management, North China Electric Power University, Baoding 071003, China |
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| Abstract: | The prediction of NOx emissions from regional thermal power plants in China is considered to be a grey system due to small sample sizes and poor information.Because of the influence of a number of factors,a single prediction model has difficulty accurately reflecting the complex changes in NOx emissions,and tends to produce large forecast errors.By using the grey forecasting and support vector machine forecasting theories,we establish a combined and optimized forecasting model for NOx emissions from thermal power plants.On the basis of the NOx emissions data issued by the authoritative departments in China,and considering the main factors which affect NOx emissions from thermal power plants,we predict NOx emissions from 2008 to 2010 and the year 2020.The predictions are roughly in accord with the actual values.Meanwhile,the necessary prediction time was greatly shortened. |
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| Keywords: | NOx emissions grey forecasting model support vector machine combination forecasting model |
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