Forecasting the transport energy demand based on PLSR method in China

Forecasting the transport energy demand based on PLSR method in China
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基于PLSR方法的中国交通能源需求预测

DOI:
10.1016/j.energy.2009.06.032
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发表时间:
2009-09
期刊:
影响因子:
9
通讯作者:
--
中科院分区:
工程技术1区
文献类型:
--
作者:

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交通运输在中国能源消费中占有很大份额,特别是石油产品,能源需求增长很快。基于偏最小二乘回归(PLSR)方法,对2010年、2015年和2020年两种情景下的交通能源需求进行预测。根据国内生产总值(GDP)、城镇化率、旅客周转量和货运周转量对1990-2006年期间的交通能源需求进行了分析。该方法表明,2020年交通能源需求将分别达到433.13 Mtce和468.26 Mtce左右。这些数字与中国能源研究所的估算非常接近。因此,本研究提供了一种有效的工具,可作为交通能源需求的替代解决方案和估算技术。
Transportation sector accounts for a major share of energy consumption in China, especially the petroleum products, which experienced rapid increases in energy demand. The purpose of this study is to forecast transport energy demand for 2010, 2015 and 2020 based on partial least square regression (PLSR) method under two scenarios. Transport energy demand is analyzed for the period of 1990–2006 based on gross domestic product (GDP), urbanization rate, passenger-turnover and freight-turnover. This method suggests that transport energy demand for 2020 will reach to a level of around 433.13Mtce and 468.26Mtce, respectively. Those figures are very close to the estimation obtained by Energy Research Institute of China. Thus this study provides an effective tool, which can be used as an alternative solution and estimation techniques for the transport energy demand.
DOI: 10.1016/j.envsoft.2005.12.007
发表时间: 2007-03
期刊: Environ. Model. Softw.
影响因子: --
作者:
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