Journal of Jilin University(Earth Science Edition) ›› 2021, Vol. 51 ›› Issue (5): 1316-1323.doi: 10.13278/j.cnki.jjuese.20200310

Previous Articles     Next Articles

Prediction of Ground Settlement Around Deep Foundation Pit Based on Stacking Model Fusion

Qin Shengwu, Zhang Yanqing, Zhang Lingshuai, Miao Qiang, Cheng Qiushi, Su Gang, Sun Jingbo   

  1. College of Construction Engineering, Jilin University, Changchun 130026, China
  • Received:2020-12-17 Online:2021-09-26 Published:2021-09-29
  • Supported by:
    Supported by the National Natural Science Foundation of China (41977221) and Jilin Provincial Science and Technology Development Project (20190303103SF)

Abstract: In order to improve the prediction ability of machine learning in ground settlement of deep foundation pit, in this study,the authors proposed a ground settlement prediction method based on multi-model combination under Stacking framework. Taking a deep foundation pit in Shenzhen as an example, the Spearman correlation coefficient was used to screen the influencing factors of foundation pit ground settlement,and the eight influencing factors were used to establish the prediction model of ground settlement of deep foundation pit, so as to verify the applicability of this method. The mean absolute error, mean absolute error percentage, and root mean square error of the Stacking prediction model are 0.34, 2.22%, and 0.13, respectively. Compared with conventional base models (random forest, support vector machines, and artificial neural networks),the mean absolute error, mean absolute error percentage and root mean square error values of the Stacking prediction model are minimum.

Key words: foundation pit construction, surface subsidence, Stacking model fusion, impact factor screening

CLC Number: 

  • TU47
[1] 胡之锋, 陈健, 邱岳峰, 等. 一种黏土层中深基坑开挖地表沉降预测方法[J]. 长江科学院院报, 2019, 36(6):60-67. Hu Zhifeng, Chen Jian, Qiu Yuefeng, et al. A Simplified Method for Predicting Ground Surface Settlement Induced by Deep Excavation of Clay Stratum[J]. Journal of Changjiang Academy of Sciences, 2019, 36(6):60-67.
[2] 魏纲, 周洋, 魏新江. 盾构隧道施工引起的工后地面沉降研究[J]. 岩石力学与工程学报, 2013, 32(增刊1):2891-2896. Wei Gang, Zhou Yang, Wei Xinjiang. Research on Post-Construction Surface Settlement Caused by Shield Tunneling[J]. Chinese Journal of Rock Mechanics and Engineering, 2013, 32(Sup.1):2891-2896.
[3] Sangyoub L, Daniel W H. Predictive Tool for Estimating Accident Risk[J]. Journal of Construction Engineering and Management, 2003, 129(4):431-436.
[4] 孙超, 许成杰. 基坑开挖对周边环境的影响[J]. 吉林大学学报(地球科学版), 2019, 49(6):1698-1705. Sun Chao, Xu Chengjie. Influence of Excavation of a Deep Excavation on the Surrounding Environment[J]. Journal of Jilin University (Earth Science Edition), 2019, 49(6):1698-1705.
[5] Yoo C, Lee D. Deep Excavation-Induced Ground Surface Movement Characteristics:A Numerical Investigation[J]. Computers and Geotechnics, 2008, 35(2):231-252.
[6] Zhou Y, Su W, Ding L, et al. Predicting Safety Risks in Deep Foundation Pits in Subway Infrastructure Projects:Support Vector Machine Approach[J]. Journal of Computing in Civil Engineering, 2017, 31(5):040170525.
[7] 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. Liu He, Zhang Hongqiang, Liu Bin. A Prediction Method for the Deformation of Deep Foundation Pit Based on Particle Swarm Optimization Neural Network[J]. Journal of Jilin University (Earth Science Edition), 2014, 44(5):1609-1614.
[8] 齐干, 朱瑞钧. 基于BP网络的基坑周围地表沉降影响因素分析[J]. 地下空间与工程学报, 2007, 3(5):863-867. Qi Gan, Zhu Ruijun. Analysis of Factors Affecting Ground Settlement Around Deep Foundation Pit Based on BP Neural Network[J]. Chinese Journal of Underground Space and Engineering, 2007, 3(5):863-867.
[9] 石祥锋, 王丽芬, 沈阳, 等. 基于GA-SVM的基坑施工地面沉降时间序列预测研究[J]. 施工技术, 2017, 46(8):16-19. Shi Xiangfeng, Wang Lifen, Shen Yang, et al. Research on Time Series Predication of Foundation Excavation Construction Land Settlement Based on the GA-SVM[J]. Construction Technology, 2017, 46(8):16-19.
[10] 林楠, 陈永良, 李伟东, 等. 极限学习机模型在季冻区深基坑地表沉降预测中的应用[J]. 世界地质, 2018, 37(4):1281-1287. Lin Nan, Chen Yongliang, Li Weidong, et al. Application of Extreme Learning Machine Model in Ground Settlement Prediction of Deep Foundation Pit in Seasonal Frozen Area[J]. Global Geology, 2018, 37(4):1281-1287.
[11] 李珩, 朱靖波, 姚天顺. 基于Stacking算法的组合分类器及其应用于中文组块分析[J]. 计算机研究与发展, 2005(5):844-848. Li Heng, Zhu Jingbo, Yao Tianshun. Combined Multiple Classifiers Based on a Stacking Algorithm and Their Application to Chinese Text Chunking[J]. Journal of Computer Research and Development, 2005(5):844-848.
[12] 王荣政, 廖贤艺, 陈湘萍, 等. 基于集成学习融合模型的血糖预测[J]. 医学信息学杂志, 2019, 40(1):59-62. Wang Rongzheng, Liao Xianyi, Chen Xiangping, et al. Blood Glucose Prediction Based on Integrated Learning Fusion Model[J]. Journal of Medical Informatics, 2019, 40(1):59-62.
[13] Jiang M Q, Liu J P, Zhang L, et al. An Improved Stacking Framework for Stock Index Prediction by Leveraging Tree-Based Ensemble Models and Deep Learning Algorithms[J]. Physica A:Statistical Mechanics and Its Applications, 2020, 541(1):122272.
[14] 史佳琪, 张建华. 基于多模型融合Stacking集成学习方式的负荷预测方法[J]. 中国电机工程学报, 2019, 39(14):4032-4042. Shi Jiaqi, Zhang Jianhua. Load Forecasting Method Based on Multi-Model by Stacking Ensemble Learning[J]. Proceedings of the CSEE, 2019, 39(14):4032-4042.
[15] 刘安强, 王子童. 基于Stacking集成学习的采空区地面塌陷危险性预测[J]. 能源与环保, 2020, 42(9):54-58. Liu Anqiang, Wang Zitong. Prediction of the Risk of Ground Collapse in Goaf Based on Stacking Integrated Learning[J]. China Energy and Environmental Protection, 2020, 42(9):54-58.
[16] Wang J, Xu J, Peng Y, et al. Prediction of Forest Unit Volume Based on Hybrid Feature Selection and Ensemble Learning[J]. Evolutionary Intelligence, 2020, 13(1):21-32.
[17] Wolpert D H. Stacked Generalization[J]. Neural Networks, 1992, 5(2):241-259.
[18] 王牧帆, 罗周全, 于琦. 基于Stacking模型的采空区稳定性预测[J]. 黄金科学技术, 2020, 28(6):894-901. Wang Mufan, Luo Zhouquan, Yu Qi. Stability Prediction of Goaf Based on Stacking Model[J]. Gold Science and Technology, 2020, 28(6):894-901.
[19] Breiman L, Random Forests[J]. Mach Learn, 2001, 45(1):5-32.
[20] Vapnik V N. The Nature of Statistical Learning Theory[M]. New York:Springer, 1995.
[21] Kasabov N, Scott N M, Tu E, et al. Evolving Spatio-Temporal Data Machines Based on the Neu Cube Neuromorphic Framework:Design Methodology and Selected Applications[J]. Neural Networks, 2016, 78(Sup.1):1-14.
[22] 谭震霖. 基于支持向量回归的地铁深基坑地表沉降预测[D]. 武汉:华中科技大学, 2019. Tan Zhenlin. Surface Subsidence Prediction of Deep Foundation Pit Based on Support Vector Regression[D]. Wuhan:Huazhong University of Science and Technology, 2019.
[23] 钟国强, 王浩, 李莉, 等. 基于SFLA-GRNN模型的基坑地表最大沉降预测[J]. 岩土力学, 2019, 40(2):792-798. Zhong Guoqiang, Wang Hao, Li Li, et al. Prediction of Maximum Settlement of Foundation Pit Based on SFLA-GRNN Model[J]. Rock and Soil Mechanics, 2019, 40(2):792-798.
[1] Sang Songkui, Wang Yonghong, Zhang Mingyi, Kong Liang, Wu Wenbing, Chen Zhixiong, Li Zhaolong, Zhang Qijun. Pore Water Pressure at Pile-Soil Interface of Jacked Pile in Silty Soil and Silty Clay [J]. Journal of Jilin University(Earth Science Edition), 2021, 51(5): 1551-1559.
[2] Wang Yonghong, Huang Yongfeng, Zhang Mingyi, Li Changhe, Su Lei, Zhang Wengang, Lin Peiyuan, Cui Jifei, Yan Zhen. Research Progress on Time Effect of Static Pressure Pile Bearing Capacity [J]. Journal of Jilin University(Earth Science Edition), 2021, 51(5): 1490-1505.
[3] Wei Jiabin, Wang Weidong, Wu Jiangbin. Numerical Simulation with FLAC3D on Ground Surface Vibration During Pile Driving Using Resonance-Free Technology [J]. Journal of Jilin University(Earth Science Edition), 2021, 51(5): 1514-1522.
[4] Wang Yonghong, Sang Songkui, Zhang Mingyi, Li Changhe, Han Bo, Yuan Bingxiang, Xiang Junning, Wang Zhenjie, Liu Huining. Analysis of Earth Pressure at Interface of Piles-Soil in Pile Sinking Under Static Pressure in Cohesive Soil [J]. Journal of Jilin University(Earth Science Edition), 2021, 51(5): 1535-1543.
[5] Ba Zhenning, Liu Bojia, Fu Jisai. Study on Scattering of Cylindrical SH Waves by a Row of Piles: Analytical Solution [J]. Journal of Jilin University(Earth Science Edition), 2021, 51(5): 1306-1315.
[6] Wang Ting, Lan Jingyan, Song Xijun, Wu Lianbin, Cai Jindou, Shi Qingqi. Characteristic Analysis of Design Response Spectrum of Sea Soft Soil Site Based on Centrifugal Model Tests [J]. Journal of Jilin University(Earth Science Edition), 2021, 51(5): 1391-1399.
[7] Cui Jifei, Rao Pingping, Li Jingpei. Influence of New Pile Penetration on Adjacent Reused Pile [J]. Journal of Jilin University(Earth Science Edition), 2021, 51(5): 1506-1513.
[8] Su Liang, Shi Wei, Shui Weihou, Cao Jianmeng. Field Test of High Energy Dynamic Compaction on Hydraulic Sandy Filling [J]. Journal of Jilin University(Earth Science Edition), 2021, 51(5): 1560-1569.
[9] Lang Qiuling, Wang Wei, Gao Chengliang. Stability Evaluation of Deep Foundation Pit of Metro Based on Grey Correlation Analysis with Combined Weights [J]. Journal of Jilin University(Earth Science Edition), 2020, 50(6): 1823-1832.
[10] Zhang Mingyi, Liu Xueying, Wang Yonghong, Bai Xiaoyu, Sang Songkui. Field Test on Influencing Mechanism of Silty Soil and Silty Clay on Tip Resistance of Static Pressure Pile [J]. Journal of Jilin University(Earth Science Edition), 2020, 50(6): 1804-1813.
[11] Li Yunong, Lehane B M. Lateral Stress for Model Jacked Piles in Two-Layered Kaolin Clay [J]. Journal of Jilin University(Earth Science Edition), 2018, 48(6): 1778-1784.
[12] Sun Chao, Shao Yanhong, Wang Handong. Research Progress and Thinking on Horizontal Frost Heaving Force and Retaining Structure [J]. Journal of Jilin University(Earth Science Edition), 2018, 48(3): 784-798.
[13] Tan Fulin, Hu Xinli, Zhang Yuming, He Chuncan, Zhang Han. Calculation Method of Landslide Thrust Considering Progressive Failure Process [J]. Journal of Jilin University(Earth Science Edition), 2018, 48(1): 193-202.
[14] Wu Youping, Zhang Keneng, Liu Jie, He Jie. Settlement Characteristics of Composite Foundation Reinforced by Flexible Piles with Lateral Restraint [J]. Journal of Jilin University(Earth Science Edition), 2017, 47(3): 818-825.
[15] Gui Yue, Yu Zhihua, Liu Haiming, Ding Zude, Zhang Qing. Suitable Compaction Moment and Strength Recovery Properties of Remodeled Stabilized Dredged Soil from Dianchi Lake [J]. Journal of Jilin University(Earth Science Edition), 2014, 44(6): 1928-1935.
Viewed
Full text


Abstract

Cited

  Shared   
  Discussed   
[1] CHENG Li-ren, ZHANG Yu-jie, ZHANG Yi-chun. Ordovician Nautiloid Fossils of Xainza Region,Tibet[J]. J4, 2005, 35(03): 273 -0282 .
[2] CHEN Li, NIE Lei, WANG Xiu-fan, LI Jin. Seismic Risk Analysis of Some Electric Power Equipment Station in Suizhong[J]. J4, 2005, 35(05): 641 -645 .
[3] LI Bin, MENG Zi-fang, LI Xiang-bo, LU Hong-xuan, ZHENG Min. The Structural Features and Depositional Systems of the Early Tertiary in the Biyang Depression[J]. J4, 2005, 35(03): 332 -0339 .
[4] ZHAO Hong-guang,SUN Jing-gui, CHEN Jun-qiang,ZHAO Jun-kang, YAO Feng-liang,DUAN Zhan. The Genesis and Evolution of Orebearing Fluids of the Xiaoxinancha Goldbearing Porphyry Copper Deposit in Yanbian Area: H,O,C,S,Pb Isotope Tracing[J]. J4, 2005, 35(05): 601 -606 .
[5] MENG Yuan-lin,GAO Jian-jun,LIU De-lai, NIU Jia-yu,SUN Hong-bin,ZHOU Yue,XIAO Li-hua,WANG Yue-chuan. Diagenetic Facies Analysis and Anomalously High Porosity Zone Prediction of the Yuanyanggou Area in the Liaohe Depression[J]. J4, 2006, 36(02): 227 -0233 .
[6] ZENG Zhao-fa, WU Yan-gang, HAO Li-bo,WANG Zhe-jiang,HUANG Hang. The Poisson’s Theorem Based Analysis Method and Application of Magnetic and Gravity Anomalies[J]. J4, 2006, 36(02): 279 -0283 .
[7] CHANG Qiu-ling, LU Xin-xiang, LIU Dong-hua, LI Ming-li. The Relation Between Gold Deposits and Wuduoshan Granite in Eastern Qinling[J]. J4, 2006, 36(03): 319 -325 .
[8] MA Yan-mei,CUI Qi-liang,ZHOU Qiang,HUANG Wei-jun,LIU Ye,PENG Gang,ZOU Guang-tian. InSitu Raman Study of Olivine Under High Temperature[J]. J4, 2006, 36(03): 342 -345 .
[9] HAO Qi,LIU Zhen, ZHA Ming, LI Chun-xia. Characters and Controlling Factors on the Archean Fracturetype Reservoirs of the Ciyutuo Buried Hill in the Liaohe Basin[J]. J4, 2006, 36(03): 384 -390 .
[10] ZENG Dao-ming, JI Hong-jin, CHEN Man,HU Da-qian, ZHU Yong-zheng. The Relationships between Geological and Geochemical Variables at Shancheng Gold Deposit in Jiaodong Area[J]. J4, 2006, 36(04): 511 -515 .