Prediction of subgrade settlement using PMIGM(1,1) model based on particle swarm optimization and Markov optimization

被引：0

作者：

Liu H.-M. ^{[1
]}

Zhou X.-G. ^{[1
]}

Wang Z.-W. ^{[2
]}

Huang D. ^{[3
]}

Yang H.-H. ^{[1
]}

机构：

[1] Yunnan Key Laboratory of Disaster Reduction in Civil Engineering, Faculty of Civil Engineering and Mechanics, Kunming University of Science and Technology, Kunming

[2] Shidian County Baoshi Expressway Investment Development Co., Ltd., Shidian

[3] Yunnan Sales Branch, Chinese National Petroleum Corporation, Kunming

来源：

Yantu Gongcheng Xuebao/Chinese Journal of Geotechnical Engineering | 2019年 / 41卷

关键词：

Grey theory; Markov Chain; Particle swarm optimization; PMIGM(1,1) model; Subgrade settlement;

D O I：

10.11779/CJGE2019S1052

中图分类号：

学科分类号：

摘要：

Accurate prediction of subgrade settlement of expressways is of great significance to their disease prevention and treatment. The previous prediction models for the subgrade settlement are mostly single models or simple improved models. A PMIGM(1,1) prediction model based on the particle swarm optimization (PSO) and Markov optimization is proposed. Firstly, based on the grey theory, an improved GM(1,1) prediction model is put forward. Then, according to the theory knowledge of Markov chains, an MIGM(1, 1) model is built to correct the relative residuals of IGM(1, 1) model, which can reflect the volatility characteristics of the data. Based on the principle of PSO, an optimization of PMIGM(1, 1) model is set up, which crystallizes the parameters of grey interval. The forecasting model is applied to a high-fill subgrade of Baoshan-Shidian Expressway in Yunnan Province. The analysis results show that the proposed model can improve the accuracy of the forecasting model. © 2019, Editorial Office of Chinese Journal of Geotechnical Engineering. All right reserved.

引用

页码：205 / 208

页数：3

共 6 条

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