灰色GM(1,1,t^(a))模型与自忆性原理的耦合及应用  

Coupling of grey GM(1,1,t^(a)) model and self-memory principle and its applications

作　　者：郭晓君[1,2] 刘思峰[1] 方志耕[1] 周伟杰[1] 

机构地区：[1]南京航空航天大学经济与管理学院,南京211106 [2]南通大学理学院,江苏南通226019

出　　处：《控制与决策》2014年第8期1447-1452,共6页Control and Decision

基　　金：国家自然科学基金项目(71111130211,71171113,71363046);国家社会科学基金重点项目(12AZD102);江苏省普通高校研究生科研创新计划项目(CXZZ13 0184);中央高校基本科研业务费专项资金;南通市科技计划项目(HS2013026)

摘　　要：针对实际工程应用中传统GM(1,1)模型预测的局限性,以含时间幂次项的灰色GM(1,1,tα)模型为基础,构建了灰色GM(1,1,tα)与自忆性原理的耦合预测模型;用动力系统自忆性原理来克服传统灰色模型对初值比较敏感的弱点;将灰色GM(1,1,t2)自忆性模型应用于某沿海高速软土地基沉降的模拟和预测,获得了满意的模拟和预测精度.实验算例表明,所提出的新模型显著地改善了传统灰色预测模型的模拟预测精度.In view of the limitation of the traditional GM（1,1） model for prediction in practical engineering application, the coupling prediction model of the grey GM（1,1,tα） and self-memory principle is constructed based on the grey GM（1,1,tα） with time power. The traditional grey model’s weakness as being sensitive to initial value can been overcomed by the self-memory principle of the dynamic system. And the grey GM（1,1,t2） self-memory model is used to fit and forecast the settlement of soft soil foundation of a certain coastal highway, which can obtain satisfactory accuracy of fitting and forecasting. Experiment results show that the proposed model can improve the fitting and forecasting accuracy of the traditional grey prediction model remarkably.

关 键 词：GM(1 1 t^(a))模型 自忆性原理 GM(1 1 t^(2))自忆性模型 软土地基沉降 

分 类 号：N941.5[自然科学总论—系统科学]