Journal of Systems Engineering and Electronics ›› 2013, Vol. 35 ›› Issue (5): 1013-1017.doi: 10.3969/j.issn.1001-506X.2013.05.19

• 系统工程 • 上一篇    下一篇

考虑合成灰数灰度性质的改进区间灰数预测模型

王大鹏1, 汪秉文1, 李睿凡2   

  1. 1. 华中科技大学控制科学与工程系, 湖北 武汉 430074;
    2. 北京邮电大学计算机学院, 北京 100876
  • 出版日期:2013-05-21 发布日期:2010-01-03

Improved prediction model of interval grey number based on the characteristics of grey degree of compound grey number

WANG Da-peng1,WANG Bing-wen1,LI Rui-fan2   

  1. 1. Department of Control Science and Engineering, Huazhong University of  Science and Technology, Wuhan 430074, China;  2. School of Computer Science, Beijing University of Posts and Telecommunications, Beijing 100876, China
  • Online:2013-05-21 Published:2010-01-03

摘要:

基于核和灰度的区间灰数预测模型,初步解决了区间灰数序列预测问题,但模型中灰度预测值的确定方法存在不足,且模型不支持误差分析。提出了合成灰数灰度的定义及其性质,据此分析了模型存在的问题,并建立灰度序列的预测模型实现灰度预测,以代替原有模型中灰度预测值的确定方法,从而改进和完善了原有区间灰数预测模型。改进模型从核和灰度两个方面同时发掘区间灰数序列的内蕴信息与发展趋势,克服了原有模型存在的不足,且支持误差分析和精度检验。算例表明了改进模型的有效性和可用性。

Abstract:

A prediction model of interval grey number based on kernel and grey degree preliminaryly solves the problem of prediction for interval grey number, while still has some model deficiencies which need to be improved in error analysis and the method of determining the predicted value of grey degree of interval grey number. These model deficiencies are analyzed based on the definition and characteristics of compound grey number which are proposed. Furthermore, a prediction model for grey degree is built instead of the original deficient method, thus the original prediction model of interval grey number is improved and perfected. The improved model can excavate both potential information and developing trend of interval grey number list from the aspects of both kernel and grey degree, thus the original model deficiencies are overcome, and error analysis and precision test are supported. Example analysis demonstrates the applicability of the improved model.