摘要
提出一种基于改进的PSO-GA混合优化算法的能源需求预测模型。首先使用通径分析方法比较影响因素对能源需求的解释力度,接着以1978-2005年的各个变量数据为训练样本进行模型的参数估计,并以2006-2011年数据为预测样本验证模型的有效性。结果显示,基于混合算法的预测模型要比单一使用PSO或GA算法的模型准确性更高。最后,通过分析各影响因素未来变化趋势,对我国2013-2015年能源需求进行了预测。
The present paper aims to develop an energy demand forecasting model based on an improved PSO-GA hybrid algorithm.The main affecting factors of energy demand include GDP,population,economic structure,urbanization rate, and energy structure.We first analyze the necessity of the five selected variables,which are the inputs of the model,via path-coefficient analysis method.Then,we obtain parameters of the proposed model by using the data from 1978 to 2005 and next verify the validity of the model using data from 2006 to 2011.Results of the study show that the precision of the model is higher compared with single optimization method,PSO or GA.Finally,we forecast China energy demand from 2012 to2015 after analyzing the trends of selected affecting factors.
出处
《科技管理研究》
CSSCI
北大核心
2014年第17期211-215,共5页
Science and Technology Management Research
关键词
能源需求
预测
PS
O-GA
通径分析
energy demand
forecasting
PSO-GA
path-coefficient analysis