DOI:

1.南通大学信息科学技术学院，交通与土木工程学院;2.南通大学信息科学技术学院;3.南通大学交通与土木工程学院

N945.1

Damping Accumulated Discrete GM(1,1) Model and its Application
Author:
Affiliation:

1.School of Information Science and Technology/ School of Transportation and Civil Engineering, Nantong University;2.School of Information Science and Technology, Nantong University;3.School of Transportation and Civil Engineering, Nantong University

Fund Project:

The National Natural Science Foundation of China General Program (61771265)；the QingLan Project of Jiangsu Province；the “226” Talent Scientific Research Project of Nantong City (131320633045); the Science and Technology Project of Nantong City (JC2021198)

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摘要:

基于阻尼累加生成算子和离散灰色预测模型的思想,本文提出了一类新的阻尼累加离散GM(1,1)模型,详细给出了模型的推导过程, 从理论上分析了与经典GM(1,1)模型、离散GM(1,1)模型以及最近提出的阻尼累加GM(1,1)模型的关系,探讨了模型的稳定性和数据适用类型分析, 并利用量子粒子群优化算法计算出最优阻尼累加参数,最后应用于两个实际案例. 结果表明新提出的阻尼累加离散GM(1,1)模型的拟合和预测误差均优于上述基准模型.

Abstract:

Based on the idea of damping accumulated generation operator and discrete grey prediction model, a new damping accumulated discrete GM (1,1) (DADGM(1,1)) model is proposed. The specific process of the new model is derived. The relationship between the DADGM(1,1) model and the GM(1,1) model, the discrete GM(1,1) model, the damping accumulated GM(1,1) model is theoretically analyzed. Stability property and the analysis of data application types of the DADGM(1,1) model are discussed, and the optimal damping accumulative parameter is searched by using the quantum particle swarm optimization algorithm. Finally, two practical examples are given. Numerical results show that the new proposed DADGM(1,1) model has better fitting and prediction efficiency than the above benchmark models.

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##### 历史
• 收稿日期:2021-10-14
• 最后修改日期:2022-02-10
• 录用日期:2022-02-25
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