An Optimal Grey-Regression Combinatorial Model and Its Applications in China Fire′s Forecasting
An Optimal Grey-Regression Combinatorial Model and Its Applications in China Fire′s Forecasting
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发表时间：
2008
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通讯作者：
Wu Lu-rong
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作者：
Wu Lu-rong
火灾每年给世界各国人民造成巨大的损失。火灾是一个具有随机性和模糊性的灰色系统的复杂行为。研究火灾的发生规律及其演变趋势具有重要的实用价值。为此，首先给出了最小二乘估计意义下的最优组合预测模型的定义，并求出了该模型的权值表达式，然后用回归分析的方法建立多个回归模型，根据以下三个标准，选出最优的非线性回归预测模型：①相关指数（主要），②系统误差③模型精度运用灰色理论建立多个灰色模型，并按照以下三个标准选择最优灰色预测模型：①误差平方商（最小），②残差概率③预测关联度（主要）;最后，利用线性最小二乘法，将灰色预测模型和回归预测模型结合起来，建立了中国火灾的最优组合预测模型组合模型预测结果表明，我国火灾发生量呈逐年动态增加趋势。
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.