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重庆交通大学学报（自然科学版）

重庆交通大学学报（自然科学版） ›› 2022, Vol. 41 ›› Issue (02): 65-70.DOI: 10.3969/j.issn.1674-0696.2022.02.10

• 交通基础设施工程 • 上一篇    下一篇

优化的分数阶GM(1,1)模型在桥梁线形控制中的应用

洪晓江1，张雪松2，郭宁1，李鸿鸣3   

  1. (1. 西昌学院 土木与水利工程学院,四川 西昌 615000； 2. 重庆交通大学 土木工程学院, 重庆 400074； 3. 成都理工大学 地质灾害防治与地质环境保护国家重点实验室, 四川 成都 610059)
  • 收稿日期:2020-08-20 修回日期:2020-12-12 发布日期:2022-02-21
  • 作者简介:洪晓江（1986—），男，四川西昌人，讲师，博士研究生，主要从事大跨度桥梁施工监控方面的研究。E-mail：hxjxcxy@126.com
  • 基金资助:
    国家自然科学基金项目（51308082）；四川省科技厅基金项目（2018GZ0499）；西昌学院“两高”计划基金项目（LGLZ201824）；西昌学院博士科研启动项目（YBZ202144）

Application of Optimized Fractional Order GM (1,1) Model in Bridge Alignment Control

HONG Xiaojiang1, ZHANG Xuesong2, GUO Ning1, LI Hongming3   

  1. (1. School of Civil Engineering and Hydraulic Engineering, Xichang University, Xichang 615000, Sichuan, China; 2. School of Civil Engineering, Chongqing Jiaotong University, Chongqing 400074, China; 3. State Key Laboratory of Geohazard Prevention and Geoenvironment Protection, Chengdu University of Technology, Chengdu 610059, Sichuan, China)
  • Received:2020-08-20 Revised:2020-12-12 Published:2022-02-21

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摘要： 针对传统灰色预测模型用于大跨径刚构桥梁预拱度预测会出现过拟合现象和预测精度不高的问题，将分数阶算子GM(1,1)模型引入大跨径桥梁预拱度预测，并建立了一种基于牛顿二次插值的分数阶GM(1,1)新模型，实现了对传统GM(1,1)模型的阶数和背景值的双重优化。为了检验模型性能，将文中模型与传统GM(1,1)模型、分数阶GM(1,1)进行对比分析。通过实例验证，优化得到的分数阶GM(1,1)的预测平均相对误差为3.1%，相比传统的GM(1,1)减小了9%，预测精度进一步得到提高。新模型具有一定的实用性，且精度较高，对于同类型的桥梁施工控制有一定的参考价值。

关键词: 桥梁工程；线形控制；预拱度；GM(1,1)预测；分数阶

Abstract: In order to solve the problems of over fitting and low prediction accuracy in the traditional grey prediction model for long-span rigid frame bridge camber prediction, the fractional order operator GM (1,1) model was introduced in long-span bridge camber prediction. And a new fractional order GM (1,1) model based on Newton quadratic interpolation was established, which realized the dual optimization of the order and background value of the traditional GM (1,1) model. To test the performance of the proposed model, the proposed model was compared with the traditional GM (1,1) model and fractional order GM (1,1) model. The example shows that the average relative error of the optimized fractional order GM (1,1) is 3.1%, which is reduced by 9% compared with the traditional GM (1,1), and the prediction accuracy is further improved. The new model has certain practicability and higher precision, and has a certain reference value for the construction control of the same type of bridge.

Key words: bridge engineering; linear control; camber; GM (1,1) prediction; fractional order

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