An Optimal Grey-Regression Combinatorial Model and Its Applications in China Fire′s Forecasting
WU Lu-rong · Shuxue de shijian yu renshi · 2008
Every year fire causes enormous losses to people in many Countries.Fire is a complex action of Grey system with random and fuzzy complexity.It is of practical value to study the rule of fire occurrence and its evolutional trend.Therefore,firstly the definition of the optimal combinatorial forecasting model was given in the sense of least square estimate and find out the expression of weight of the above mentioned model,and to prove it to be unique;then the optimal nonlinear regression forecasting model was selected by establishing several regression models by means of regression analysis and in accordance to the following three standards:① index of correlation (the major),② error of system(the minor),③ precision of model(the major),and the optimal gray forecasting model was selected by establishing several gray models by means of gray theory,and in accordance with the following three standards: ① quotient of square error(the least),② probability of residual error(the major),③ forecasting relative degree(the major);and finally an optimal combinatorial forecasting model for fire in China has been established through combining the Grey and regression models by means of linear least square algorithms.The combinatorial forecasting model combines the two sources of information together,thus improving and expanding the corresponding field for Grey model regression model,and making the results better and accurate.The combinatorial model forecasts that fire in China occurs on a dynamic increase trend year after year.