[1]崔凯,秦晓同,荆祥.季节性冻土区路基高边坡变形多因素时变预测模型[J].哈尔滨工程大学学报,2019,40(06):1109-1114.[doi:10.11990/jheu.201804113]
 CUI Kai,QIN Qiaotong,JING Xiang.Multifactor time-varying model for the prediction of subgrade high-slope deformation in areas with seasonally frozen soil[J].hebgcdxxb,2019,40(06):1109-1114.[doi:10.11990/jheu.201804113]
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《哈尔滨工程大学学报》[ISSN:1006-6977/CN:61-1281/TN]

卷:
40
期数:
2019年06期
页码:
1109-1114
栏目:
出版日期:
2019-06-05

文章信息/Info

Title:
Multifactor time-varying model for the prediction of subgrade high-slope deformation in areas with seasonally frozen soil
作者:
崔凯1 秦晓同2 荆祥2
1. 西南交通大学 高速铁路线路工程教育部重点实验室, 四川 成都 610031;
2. 西南交通大学 土木工程学院, 四川 成都 610031
Author(s):
CUI Kai1 QIN Qiaotong2 JING Xiang2
1. Key Laboratory of High-speed Railway Engineering of the Ministry of Education, Southwest Jiaotong University, Chengdu 610031, China;
2. School of Civil Engineering, Southwest Jiaotong University, Chengdu 610031, China
关键词:
季节性冻土区路基高边坡变形多因素监测数据时变预测支持向量机理论
分类号:
U213.1
DOI:
10.11990/jheu.201804113
文献标志码:
A
摘要:
为了研究季节性冻土区路基在各种影响因素作用下的运营质量,本文对路基高边坡进行沉降变形预测研究。鉴于当前路基变形各种预测模型均有其适用范围,总体预测波动性较大,精度较低,提出了一种基于支持向量机的季节性冻土区路基高边坡变形多因素时变预测模型。依托季节性冻土区路基观测系统,在分析相关监测数据的基础上,对季节性冻土区路基高边坡变形特征及其热稳定性影响因素进行分析,并总结主要因素对高边坡路基变形的影响规律。借助该周期性变化规律采用支持向量机理论构建了变形多因素时变预测模型。实验结果表明:本文模型在预测精度上较当前预测模型在预测精度上有所提高,可为岩土工程建设提供重要的参考依据。

参考文献/References:

[1] 靳鹏伟, 何永红. 改进灰色模型高铁隧道路基沉降分析与预测[J]. 铁道科学与工程学报, 2016, 13(12):2355-2359.JIN Pengwei, HE Yonghong. Settlement analysis and predictation of high-speed rail tunnel subgrade based on the improved Gray model[J]. Journal of railway science and engineering, 2016, 13(12):2355-2359.
[2] SU Huaizhi, YANG Meng, WEN Zhiping, et al. Deformation-based safety monitoring model for high slope in hydropower project[J]. Journal of civil structural health monitoring, 2016, 6(5):779-790.
[3] 崔凯, 杨文恒. 软土路基沉降的联合法预测研究[J]. 西南交通大学学报, 2017, 52(5):926-934.CUI Kai, YANG Wenheng. Prediction soft soil settling using a combination method[J]. Journal of Southwest Jiaotong University, 2017, 52(5):926-934.
[4] LEUNG A K, NG C W W. Field investigation of deformation characteristics and stress mobilisation of a soil slope[J]. Landslides, 2016, 13(2):229-240.
[5] 姜献东, 张苏俊, 卢佩霞. 灰色系统模型在软土路基沉降预测中的应用[J]. 施工技术, 2016, 45(5):81-83.JIANG Xiandong, ZHANG Sujun, LU Peixia. The application of grey system model in settlement prediction of soft soil subgrade[J]. Construction technology, 2016, 45(5):81-83.
[6] 靳鹏伟, 何永红, 陈青海. 马尔可夫残差修正模型的高铁路基变形预测[J]. 测绘科学, 2017, 42(7):84-88.JIN Pengwei, HE Yonghong, CHEN Qinghai. Deformation prediction of high speed railway subgrade based on Markov besidual error correction model[J]. Science of surveying and mapping, 2017, 42(7):84-88.
[7] SALOUR F, ERLINGSSON S. Permanent deformation characteristics of silty sand subgrades from multistage RLT tests[J]. International journal of pavement engineering, 2017, 18(3):236-246.
[8] 陈良琼. 基于最大Lyapunov指数的公路沉降预测[J]. 信阳师范学院学报(自然科学版), 2017, 30(4):647-650.CHEN Liangqiong. Forecasting for settlement of highway on Lyapunov exponents[J]. Journal of Xinyang Normal University (natural science edition), 2017, 30(4):647-650.
[9] 周伟杰, 张宏如, 党耀国, 等. 新息优先累加灰色离散模型的构建及应用[J]. 中国管理科学, 2017, 25(8):140-148.ZHOU Weijie, ZHANG Hongru, DANG Yaoguo, et al. New information priority accumulated grey discrete model and its application[J]. Chinese journal of management science, 2017, 25(8):140-148.
[10] 次旦多杰. 基于冻土特征的青藏公路路基病害分析[J]. 筑路机械与施工机械化, 2017, 34(10):90-93.CIDAN Duojie. Analysis of subgrade diseases of Qinghai-Tibet highway based on features of permafrost[J]. Road machinery & construction mechanization, 2017, 34(10):90-93.

备注/Memo

备注/Memo:
收稿日期:2018-04-30。
基金项目:国家自然科学基金项目(41572245).
作者简介:崔凯,男,教授,博士生导师.
通讯作者:崔凯,E-mail:cuikai@swjtu.cn.
更新日期/Last Update: 2019-06-03