Combining forecasting model based on Grey theory and artificial neural network

被引：0

作者：

Zheng Deling ^{[1
]}

Liu Cong ^{[1
]}

Fang Wei ^{[1
]}

Fang Tong ^{[1
]}

机构：

[1] Univ Sci & Technol Beijing, Sch Informat Engn, Beijing 100083, Peoples R China

来源：

Proceedings of the 24th Chinese Control Conference, Vols 1 and 2 | 2005年

关键词：

Grey theory; residual modification; artificial neural network; combining forecasting;

D O I：

暂无

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

Grey theory is broadly applied to model and prediction of systems that characterized by poor information. The GM residual model is more adaptive to practical forecasting than GM(1,1) due to the precision problem. However, the potency of residual series depends on the number of data points with the same sign. This paper presents a technique that combines residual modification with artificial neural network sign estimation, which widens residual model's application range. Also, based on the combining forecasting theory, an integrated ANN and grey model were be defined which Supplies an effective method for further improving prediction accuracy.

引用

页码：1069 / 1072

页数：4