GM(1,1)模型的性质及改进

doi:10.6040/j.issn.1671-9352.4.2021.227

摘要/Abstract

摘要： 在对GM(1,1)模型进行分析的基础上,经过理论推导,得出了初始数对预测没有影响的结论,对GM(1,1)模型进行改进,给出了GM(1,1)模型Ⅰ。当向原始序列添加相同的数字时,预测值将更改,由此提出了GM(1,1)模型Ⅱ,利用粒子群算法,得到最佳的增加量。仿真结果表明,GM(1,1)模型Ⅰ和模型Ⅱ具有较高的精度。

关键词: GM(1,1)模型, 简化, 精度, 粒子群优化算法

Abstract: Based on theoretical analysis of GM(1,1)model, the conclusion, which the initiative number has no effect on the prediction, is got. GM(1,1)model is improved and GM(1,1)model I is given. When add an identical number to the original series, the forecast values will change. GM(1, 1)model Ⅱ is given, and using particle swarm algorithm, the best increase is got. Simulation results show that the improved GM(1, 1)model Ⅰ and GM(1, 1)model Ⅱ have higher accuracy.

Key words: GM(1,1)model, simplify, precision, particle swarm algorithm

中图分类号:

N941.5

潘澔,高尚. GM(1,1)模型的性质及改进[J]. 《山东大学学报(理学版)》, 2021, 56(11): 38-42.

PAN Hao, GAO Shang. Properties and improvement of GM(1,1)models[J]. JOURNAL OF SHANDONG UNIVERSITY(NATURAL SCIENCE), 2021, 56(11): 38-42.

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