灰色最小二乘马尔可夫链预测算法  

Grey-Least Square Method-Markov Chain Algorithm for Forecasting

作　　者：李志俊[1] 范斐斐[1] 陈绵云[2] 张洁[1] 

机构地区：[1]武汉理工大学自动化学院,湖北武汉430070 [2]华中科技大学控制科学与工程系,湖北武汉430074

出　　处：《武汉理工大学学报（信息与管理工程版）》2008年第1期59-62,82,共5页Journal of Wuhan University of Technology：Information & Management Engineering

基　　金：国家自然科学基金资助项目(70471031);国防预研基金资助项目(00J15.3.3.JW0528)

摘　　要：科学的预测对于经济现象的研究和经济决策的制定都具有十分重要的意义,因此,关于经济预测理论和方法的研究一直是一个热点。将灰色模型预测方法GM(l,l)、最小二乘法与马尔可夫链预测相结合,提出灰色最小二乘马尔可夫链改进预测方法,并且针对我国能源消费总量的发展趋势进行了预测,得出比灰色预测更加准确的结论。从而证明,灰色最小二乘马尔可夫链改进方法是个好算法,更有利于决策者的经济决策行为。Scientific forecast is of great importance to the economic phenomenon research and decision -making. Therefore, the research on economic forecast theory and method has always been a hot topic. The grey model, least square method and markov chains for forecasting were combined, and the approaches for forecast improvement of the least square method were proposed. Aiming at the tendency of the gross amount of energy sources consumption of our country, a conclusion was reached that the new algorithm is more accurate than the grey model. It proves that the grey - least square method - markov chain algorithm is a good one which can be helpful for policy makers in making economic decision.

关 键 词：能源消费总量 灰色预测 马尔可夫链 最小二乘法 

分 类 号：N941.5[自然科学总论—系统科学]