| GM(1,1)模型的性质及改进 |
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| 引用本文： | 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. DOI: 10.6040/j.issn.1671-9352.4.2021.227 |
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| 作者姓名： | 潘澔 高尚 |
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| 作者单位： | 1.苏州建设交通高等职业技术学校, 江苏 苏州 215104;2.江苏科技大学计算机科学与工程学院, 江苏 镇江 212003 |
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| 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。
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| 关 键 词： | GM(1 1)模型 简化 精度 粒子群优化算法 |
Properties and improvement of GM(1,1)models |
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| PAN Hao,GAO Shang. Properties and improvement of GM(1,1)models[J]. Journal of Shandong University, 2021, 56(11): 38-42. DOI: 10.6040/j.issn.1671-9352.4.2021.227 |
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| Authors: | PAN Hao GAO Shang |
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| Affiliation: | 1. Suzhou Institute of Construction &Communications, Suzhou 215104, Jiangsu, China;2. School of Computer Science and Engineering, Jiangsu University of Science and Technology, Zhenjiang 212003, Jiangsu, China |
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| 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. |
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| Keywords: | GM(1 1)model simplify precision particle swarm algorithm |
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