摘要
组合预测对于信息不完备的复杂经济系统具有一定的实用性。鉴于能源消费系统的复杂性和非线性特征,利用我国能源消费的历史数据,采用灰色预测的GM(1,1)、无偏GM(1,1)和pGM(1,1)3种模型与人工神经网络进行优化组合,建立了灰色神经网络的能源消费组合预测模型,实证分析结果获得了更为精确的预测效果,可以作为能源消费预测的有效工具。同时,能源消费的预测结果也表明今后必须以节能为主导思想,努力建设资源节约型社会和环境友好型社会。
Combination forecasting model were practicable in complex economic system with uncompleted information. Because energy consumption system was of complexity and non - linearity, this paper combined neural network and three models of GM( 1,1 ), WPGM( 1, 1), pGM(1,1) with energy consumption data, and proposed the combination forecasting model of energy consumption. The result showed that this model could gain optimized forecasting value and could be taken as an effective tool to predict future energy consumption. Mean- while, the forecasting value implied that it was strongly essential to construct resource- saving and environment - friendly society in terms of energy - saving.
出处
《资源开发与市场》
CAS
2006年第3期216-219,共4页
Resource Development & Market
基金
国家自然科学基金资助项目(40535026)
关键词
灰色神经网络
能源消费
组合预测模型
gray neural network
energy consumption
combination forecasting model