广西工学院学报2011，Vol.22Issue(4)：69-73,5.
基于累积法和背景值优化的改进GOM（1，1）模型
An Improved GOM （1,1） Model Based on Accumulative Method and Background Value Optimization
摘要
Abstract
The precision of GOM （1,1） model is influenced by the values of background value parameter identification. Based on the exponential feature of accumulated series in opposite direction and the geometric significance of background value, the background value of GOM （ 1,1 ） model is optimized and the corresponding algorithm is presented, and the parameter identification of the model is completed by accumulative method. Thus a new GOM （1,1） is presented with characteristics of simplicity and easiness for programming. Comparison experiment of precision shows that for prediction on non-negative monotone decreasing series, the prediction precision of the presented method is better than GM（ 1, ）, which verifies that our improvements are efficient.关键词
灰色GOM（1,/1）模型/背景值/累积法/优化设计Key words
Grey GOM （1,1） model/background value/accumulative method/optimal design分类
计算机与自动化引用本文复制引用
夏冬雪,陈望明,蒋建兵,周玖..基于累积法和背景值优化的改进GOM（1，1）模型[J].广西工学院学报,2011,22(4):69-73,5.基金项目
广西科学研究与开发计划项目(桂科攻0992006-13) （桂科攻0992006-13）
广西工学院科学基金项目(院科自0977211)资助. （院科自0977211）
