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中文摘要：
北京市能源需求系统具有非线性、历史数据较少而影响因素众多等复杂特征，而支持向量机模型在解决小样本、非线性及高维模式识别问题方面具有突出优势。为此，引人支持向量机模型对北京市1978--2010年能源需求进行建模．并据此对2012--2020年能源需求量进行预测。结果表明：支持向量机模型能有效拟合北京市能源需求系统的复杂变化趋势，比其他传统方法有更高的预测精度。研究发现，2012--2020年北京市能源需求量逐年增加，年均增速2．75％；另外，北京市能源需求的增速在“十三五”期间会比“十二五”期间略有趋缓。
英文摘要：
The energy demand system of Beijing has a number of features including nonlinearity,limited historical data and numerous drivers,while the Support Vector Machine（SVM） model owns unique advantage in small samples,nonlinear and high-dimensional pattern recognition.Therefore,the SVM model is employed to fit the related historical data about energy demand in Beijing from 1978—2010 and then project the energy demand during 2012—2020.The results indicate that the projection power of SVM model evidently outweighs that of other traditional and commonly-used models,which can effectively consider the complex features in energy demand system of Beijing.Additionally,the projection results also suggest that Beijing＇s energy demand may increase year by year during 2012—2020,with the average annual growth rate 2.75%;and its growth rate may appear relatively slower in the 13th Five-Year Plan period than that in the 12th Five Year Plan period.
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