地铁车站深基坑的变形预测及稳定性研究
|
摘要
为实现基坑变形预测及稳定性的综合研究,先以极限学习机(ELM)神经网络和灰色模型为基础,建立了基坑变形的串联、并联和混联耦合预测模型,以实现基坑变形预测;其次,再利用尖点突变理论和Mann-Kendall检验对基坑稳定性及变形趋势进行综合判断,以佐证预测结果的准确性。实例检验结果表明:3种耦合模型均能不同程度地提高预测精度,且以混联式模型的预测稳定性最高,其次是并联式模型和串联式模型;同时,预测结果与尖点突变理论和Mann-Kendall检验的分析结果相符,验证了该预测思路的有效性和可行性。研究方法可为基坑的变形预测提供一种的新思路。
In an attempt to comprehensively research the deformation prediction and stability of foundation pit,the series model,parallel model and parallel-serial coupled prediction model of foundation pit deformation are established on the basis of limit learning machine( ELM neural network) and grey model. Furthermore,the cusp catastrophe theory and Mann-Kendall test are employed to predict the stability and deformation trend of foundation pit to verify the correctness of prediction results. Case study show that the series model,parallel model and parallel-serial coupled model could all enhance prediction accuracy,among which the parallel-serial coupled model is of the highest stability,followed by parallel model and then serial model. In addition,the prediction results are in consistency with those by cusp catastrophe theory and Mann-Kendall test,indicating the effectiveness and feasibility of the present prediction method.
In an attempt to comprehensively research the deformation prediction and stability of foundation pit,the series model,parallel model and parallel-serial coupled prediction model of foundation pit deformation are established on the basis of limit learning machine( ELM neural network) and grey model. Furthermore,the cusp catastrophe theory and Mann-Kendall test are employed to predict the stability and deformation trend of foundation pit to verify the correctness of prediction results. Case study show that the series model,parallel model and parallel-serial coupled model could all enhance prediction accuracy,among which the parallel-serial coupled model is of the highest stability,followed by parallel model and then serial model. In addition,the prediction results are in consistency with those by cusp catastrophe theory and Mann-Kendall test,indicating the effectiveness and feasibility of the present prediction method.
引文
[1]林楠,李伟东,张文春,等.最小二乘支持向量机在深基坑变形预测中的应用[J].辽宁工程技术大学学报(自然科学版),2014,33(11):1471-1474.
[2]赵健赟,哈华林,宋宜容.利用BP-ANN模型进行深基坑变形预测分析的探讨[J].施工技术,2015,44(7):87-89.
[3]任丽芳,李立增,陈艳国,等.基于遗传算法和神经网络的润扬长江大桥深基坑变形预测[J].铁道建筑,2013,(8):44-46.
[4]刘贺,张弘强,刘斌.基于粒子群优化神经网络算法的深基坑变形预测方法[J].吉林大学学报(地球科学版),2014,44(5):1609-1614.
[5]郑知斌,刘勇,刘继尧,等.基于神经网络的基坑变形预测及安全控制研究[J].铁道工程学报,2010,27(9):64-68.
[6]张永磊,何秀凤.改进离散灰色模型在基坑周围地面沉降预测中的应用[J].工程勘察,2013,41(2):63-65,70.
[7]吴杰,柏林,左工,等.多因素灰色G(1,N)模型及其在基坑位移预测中的应用[J].测绘科学,2012,37(6):178-180.
[8]周超,殷坤龙,黄发明.混沌序列WA-ELM耦合模型在滑坡位移预测中的应用[J].岩土力学,2015,36(9):2674-2680.
[9]李胜,韩永亮,高宏,等.边坡变形的LMD-ELM多尺度预测模型研究[J].中国安全科学学报,2015,25(11):16-21.
[10]吴飞宇.基于灰色神经网络模型的基坑变形预测研究[J].测绘通报,2013,(增):189-191,286.
[11]马玉杰.公路隧道施工围岩稳定极限位移预测模型研究[D].北京:北京交通大学,2014.
[12]高彩云,崔希民.滑坡变形预测灰色神经网络耦合模型的构建及适用性分析[J].大地测量与地球动力学,2015,35(5):835-839.
[13]王博,商岸帆,郭晨,等.小波神经网络在基坑变形预测的研究与应用[J].计算机工程与应用,2012,48(19):225-229.
[14]何忠明,刘森峙,胡庆国,等.基于尖点突变理论的路堤填筑下伏溶洞顶板稳定性研究[J].中南大学学报(自然科学版),2016,47(7):2456-2462.
[15]史俊涛,孔思丽,贺俊,等.基于尖点突变理论的非均质土坡失稳判据分析[J].长江科学院院报,2015,32(5):115-120.
[16]王志鹏,孙建生,赵丹.基于突变理论的复杂地基重力坝深层抗滑稳定研究[J].长江科学院院报,2016,33(7):132-136.
[17]隆然,庞建成.基于松散型小波神经网络的某隧道仰坡变形趋势研究[J].路基工程,2016,(3):25-30.
[2]赵健赟,哈华林,宋宜容.利用BP-ANN模型进行深基坑变形预测分析的探讨[J].施工技术,2015,44(7):87-89.
[3]任丽芳,李立增,陈艳国,等.基于遗传算法和神经网络的润扬长江大桥深基坑变形预测[J].铁道建筑,2013,(8):44-46.
[4]刘贺,张弘强,刘斌.基于粒子群优化神经网络算法的深基坑变形预测方法[J].吉林大学学报(地球科学版),2014,44(5):1609-1614.
[5]郑知斌,刘勇,刘继尧,等.基于神经网络的基坑变形预测及安全控制研究[J].铁道工程学报,2010,27(9):64-68.
[6]张永磊,何秀凤.改进离散灰色模型在基坑周围地面沉降预测中的应用[J].工程勘察,2013,41(2):63-65,70.
[7]吴杰,柏林,左工,等.多因素灰色G(1,N)模型及其在基坑位移预测中的应用[J].测绘科学,2012,37(6):178-180.
[8]周超,殷坤龙,黄发明.混沌序列WA-ELM耦合模型在滑坡位移预测中的应用[J].岩土力学,2015,36(9):2674-2680.
[9]李胜,韩永亮,高宏,等.边坡变形的LMD-ELM多尺度预测模型研究[J].中国安全科学学报,2015,25(11):16-21.
[10]吴飞宇.基于灰色神经网络模型的基坑变形预测研究[J].测绘通报,2013,(增):189-191,286.
[11]马玉杰.公路隧道施工围岩稳定极限位移预测模型研究[D].北京:北京交通大学,2014.
[12]高彩云,崔希民.滑坡变形预测灰色神经网络耦合模型的构建及适用性分析[J].大地测量与地球动力学,2015,35(5):835-839.
[13]王博,商岸帆,郭晨,等.小波神经网络在基坑变形预测的研究与应用[J].计算机工程与应用,2012,48(19):225-229.
[14]何忠明,刘森峙,胡庆国,等.基于尖点突变理论的路堤填筑下伏溶洞顶板稳定性研究[J].中南大学学报(自然科学版),2016,47(7):2456-2462.
[15]史俊涛,孔思丽,贺俊,等.基于尖点突变理论的非均质土坡失稳判据分析[J].长江科学院院报,2015,32(5):115-120.
[16]王志鹏,孙建生,赵丹.基于突变理论的复杂地基重力坝深层抗滑稳定研究[J].长江科学院院报,2016,33(7):132-136.
[17]隆然,庞建成.基于松散型小波神经网络的某隧道仰坡变形趋势研究[J].路基工程,2016,(3):25-30.