摘要
用差分格式将灰色模型 GM(1,1)模型推广为 GM(1,1,λ)模型 ,λ=0 .5即为 GM(1,1)模型 ;由于参数λ与误差之间存在明显的非线形特性 ,而且某些目标函数不可微 ,使得传统的优化方法无能为力 ,文中应用遗传算法求解最优的 λ值 ,然后进行预测 .由 λ的取值知 ,GM(1,1,λ)模型的预测精度一定比 GM(1,1)高 ,数值计算的结果也证实了这一点 .
The Gray Model (GM(1,1)) has been improved with the difference scheme and a new Gray Model GM(1,1,λ) has been constructed in this paper. If λ=0.5 the model GM(1,1,λ) is the model GM(1,1).Because of the nonlinear traits between parameter λ and the errors of forecasting and nondifferentiability of object functions, the traditional optimal methods can not solve it. So the Genetic Algorithm has been applied to solving the value of λ and the prime data are forecasted according to λ. In fact, from the value of λ, a conclusion can be drawn that the accuracy of GM(1,1,λ) is much higher than that of the GM(1,1). Some practical examples show the effect of the method is remarkable.
出处
《系统工程学报》
CSCD
2000年第2期168-172,共5页
Journal of Systems Engineering