摘要
经济指标的准确预测是制定经济政策、计划、调整经济结构的必要前提。文章运用灰色系统关联度分析理论,以国内生产总值(GDP)为内部特征因素,以工业、批发零售业和金融业的产值作为主要影响因素变量,构建一个优化的多维灰色GM(1,N)模型,对我国GDP的发展进行模拟和预测。结果表明:所建立的模型对数据的拟合精确度高于传统模型,能给相关部门的决策提供一定的理论参考。
The accurate prediction of economic indicators is a necessary prerequisite for formulating economic policies and plans,and adjusting economic structure.This paper uses the grey system correlation analysis theory,takes GDP as the internal characteristic factor,and the output value of industry,wholesale and retail trade and finance industry as the main influencing factor variables,to construct an optimized multidimensional GM(1,N)model so as to simulate and forecast the development of GDP.The results show that the proposed model has higher fitting accuracy than the traditional model,which can provide a certain theoretical reference for the decision-making of relevant departments.
作者
吴鹏
邱赛兵
Wu Peng;Qiu Saibing(Keller Graduate School of Management,DeVry University,San Francisco CA94560,USA;School of Mathematics and Statistics,Hunan University of Finance and Economics,Changsha 410205,China)
出处
《统计与决策》
CSSCI
北大核心
2020年第3期42-45,共4页
Statistics & Decision
基金
国家自然科学基金面上项目(71873045)
国家社会科学基金青年项目(16CGL004)
湖南省教育厅科学研究重点项目(18A440)。
关键词
关联分析
多维灰色模型
经济预测
correlation analysis
multidimensional grey model
economic prediction
