摘要
为了提高灰色GM(1,1)幂模型的拟合精度,对灰色GM(1,1)幂模型的背景值进行了改进,建立了一类改进GM(1,1)幂模型.利用粒子群优化算法给出了改进GM(1,1)幂模型的参数优化.实例分析结果表明基于粒子群算法的改进的GM(1,1)幂模型具有更高的预测和拟合精度.
In order to improve the precision of GM(1,1) power model,the improve GM(1,1) power model is established based on the background value optimum.The particle optimization algorithm is applied to solve the improve GM(1,1) power model.The application example indicates that the precision of improve GM(1,1) power model is higher than the GM(1,1) power model.So this method is feasible,effective and has important theory significance.
出处
《纯粹数学与应用数学》
CSCD
2011年第6期711-714,共4页
Pure and Applied Mathematics
基金
国家社科基金西部项目(11XTJ001)
关键词
灰色GM(1
1)幂模型
背景值
粒子群算法
拟合精度
GM(1
1) power model
background value
particle optimization algorithm
fitting precision