摘要
GRM(1,1)是适用于非负递减数列的一种灰色预测模型.它通过对原始数据列的倒数累加生成变换及对离散点处灰导数背景值的加权处理,改善了GM(1,1)的模型精度.尝试通过对离散点处灰导数的加权处理,来改进倒数累加灰色模型GRM(1,1)的精度.实例表明,改进的倒数累加灰色模型在模型精度和预测精度上都较原模型有了很大的提高.
GRM （ 1,1 ） is a grey forecasting model applied in non-negative descending series. The precision of the model GM （ 1,1 ） can be improved by means of reciprocal accumulation generation transform for the original series and weighting operation of the background values of grey derivatives at the discrete points. In order to increase the model＇s precision further, an atempt of the improvement is made. The examples, show that the improved model has higher precision than that of the GRM （ 1,1 ） in fitting and forecasting.
出处
《沈阳理工大学学报》
CAS
2008年第4期84-86,共3页
Journal of Shenyang Ligong University
关键词
倒数累加
灰色模型
预测精度
reciprocal accumulation
grey model
forecasting precision
