Volume 39 Issue 5
Oct.  2025
Turn off MathJax
Article Contents
Article Navigation >  GEOTECHNICAL ENGINEERING TECHNIQUE  > 2025  >  39(5): 648-655
Yan Junsong, Shi Quanbin, Liu Rubing. Improved adaptive exponential smoothing method and its application evaluation in excavation deformation prediction[J]. GEOTECHNICAL ENGINEERING TECHNIQUE, 2025, 39(5): 648-655. doi: 10.20265/j.cnki.issn.1007-2993.2024-0168
Citation: Yan Junsong, Shi Quanbin, Liu Rubing. Improved adaptive exponential smoothing method and its application evaluation in excavation deformation prediction[J]. GEOTECHNICAL ENGINEERING TECHNIQUE, 2025, 39(5): 648-655. doi: 10.20265/j.cnki.issn.1007-2993.2024-0168
shu

Improved adaptive exponential smoothing method and its application evaluation in excavation deformation prediction

doi: 10.20265/j.cnki.issn.1007-2993.2024-0168

  • Institute of Architectural Engineering, Taizhou Polytechnic College, Taizhou 225300, Jiangsu, China

  • Received Date: 2024-04-16
  • Accepted Date: 2024-10-29
  • Rev Recd Date: 2024-07-29
  • Publish Date: 2025-10-10
    Abstract
  • Reliable prediction of excavation deformation contributes to improved construction safety. The existing adaptive exponential smoothing method has been improved by abandoning the traditional approach of solving for the optimal smoothing coefficient α through exhaustive search. Instead, mean squared error (MSE) was used as the loss function, and the gradient expressions of MSE with respect to α for single, double, and triple exponential smoothing models were derived. Subsequently, the gradient descent method is applied to solve for the optimal α value. Compared to the original method, the improved method demonstrates comparable performance in optimal model selection and coefficient optimization, and significantly enhances optimization efficiency with appropriate hyper-parameter (especially learning rate) settings. Based on the application to 1900 sets of excavation deformation sequences, the applicability and reliability of the improved adaptive exponential smoothing method in deformation prediction have been systematically evaluated, and the effects of prediction step size and training sequence length on prediction performance have been explored. Consequently, an optimized scheme for excavation deformation prediction is proposed.

     

    • FullText(HTML)
  • loading
    • References(24)
  • [1]
    周红波, 高文杰, 蔡来炳, 等. 基于WBS-RBS的地铁基坑故障树风险识别与分析[J]. 岩土力学, 2009, 30(9): 2703-2707,2726. (ZHOU H B, GAO W J, CAI L B, et al. Risk identification and analysis of subway foundation pit by using fault tree analysis method based on WBS-RBS[J]. Rock and Soil Mechanics, 2009, 30(9): 2703-2707,2726. (in Chinese)

    ZHOU H B, GAO W J, CAI L B, et al. Risk identification and analysis of subway foundation pit by using fault tree analysis method based on WBS-RBS[J]. Rock and Soil Mechanics, 2009, 30（9）: 2703-2707,2726. (in Chinese)
    [2]
    胡 冬, 张小平. 基于灰色系统理论的基坑变形预测研究[J]. 地下空间与工程学报, 2009, 5(1): 74-78,168. (HU D, ZHANG X P. Research on predicting deformation of foundation pit based on grey system theory[J]. Chinese Journal of Underground Space and Engineering, 2009, 5(1): 74-78,168. (in Chinese)

    HU D, ZHANG X P. Research on predicting deformation of foundation pit based on grey system theory[J]. Chinese Journal of Underground Space and Engineering, 2009, 5（1）: 74-78,168. (in Chinese)
    [3]
    CUI D G, ZHU C Q, LI Q F, et al. Research on deformation prediction of foundation pit based on PSO-GM-BP model[J]. Advances in Civil Engineering, 2021, 2021: 8822929. doi: 10.1155/2021/8822929
    [4]
    LIU Q, YANG C Y, LIN L. Deformation prediction of a deep foundation pit based on the combination model of wavelet transform and gray BP neural network[J]. Mathematical Problems in Engineering, 2021, 2021: 2161254.
    [5]
    刘俊城, 谭 勇, 张生杰. 地铁车站深基坑开挖变形智能多步预测方法[J]. 上海交通大学学报, 2024, 58(7): 1108-1117. (LIU J C, TAN Y, ZHANG S J. Multi-step prediction of excavation deformation of subway station based on intelligent algorithm[J]. Journal of Shanghai Jiao Tong University, 2024, 58(7): 1108-1117. (in Chinese)

    LIU J C, TAN Y, ZHANG S J. Multi-step prediction of excavation deformation of subway station based on intelligent algorithm[J]. Journal of Shanghai Jiao Tong University, 2024, 58（7）: 1108-1117. (in Chinese)
    [6]
    ZHAO H J, LIU W, SHI P X, et al. Spatiotemporal deep learning approach on estimation of diaphragm wall deformation induced by excavation[J]. Acta Geotechnica, 2021, 16(11): 3631-3645. doi: 10.1007/s11440-021-01264-z
    [7]
    许 莉, 林 鑫, 徐 杨, 等. 深基坑地下连续墙支护结构侧向变形的改进指数平滑法预测[J]. 应用基础与工程科学学报, 2024, 32(4): 1094-1107. (XU L, LIN X, XU Y, et al. Prediction of lateral deformation of diaphragm wall support structures in the deep foundation pit by using improved exponential smoothing method[J]. Journal of Basic Science and Engineering, 2024, 32(4): 1094-1107. (in Chinese)

    XU L, LIN X, XU Y, et al. Prediction of lateral deformation of diaphragm wall support structures in the deep foundation pit by using improved exponential smoothing method[J]. Journal of Basic Science and Engineering, 2024, 32（4）: 1094-1107. (in Chinese)
    [8]
    苏 勇, 高政国, 廖翌棋. 基于监测数据的几种地铁施工变形预测方法[J]. 岩土工程技术, 2009, 23(4): 172-177. (SU Y, GAO Z G, LIAO Y Q. Several deformation forecasting methods for metro construction based on monitoring data[J]. Geotechnical Engineering Technique, 2009, 23(4): 172-177. (in Chinese)

    SU Y, GAO Z G, LIAO Y Q. Several deformation forecasting methods for metro construction based on monitoring data[J]. Geotechnical Engineering Technique, 2009, 23（4）: 172-177. (in Chinese)
    [9]
    程 胜. 基于KF-ES融合模型的地铁基坑沉降变形预测[J]. 测绘与空间地理信息, 2023, 46(10): 161-164,167. (CHENG S. Prediction of subway foundation pit settlement and deformation based on KF-ES fusion model[J]. Geomatics & Spatial Information Technology, 2023, 46(10): 161-164,167. (in Chinese)

    CHENG S. Prediction of subway foundation pit settlement and deformation based on KF-ES fusion model[J]. Geomatics & Spatial Information Technology, 2023, 46（10）: 161-164,167. (in Chinese)
    [10]
    吴德会. 动态指数平滑预测方法及其应用[J]. 系统管理学报, 2008, 17(2): 151-155. (WU D H. Dynamic exponential smoothing prediction method and its applications[J]. Journal of Systems & Management, 2008, 17(2): 151-155. (in Chinese)

    WU D H. Dynamic exponential smoothing prediction method and its applications[J]. Journal of Systems & Management, 2008, 17（2）: 151-155. (in Chinese)
    [11]
    叶德谦, 王 毅. 一种对二次指数平滑预测中参数和初值的研究[J]. 燕山大学学报, 2008, 32(2): 173-175. (YE D Q, WANG Y. Study on choosing coefficient of secondary exponential smoothing and initial value[J]. Journal of Yanshan University, 2008, 32(2): 173-175. (in Chinese)

    YE D Q, WANG Y. Study on choosing coefficient of secondary exponential smoothing and initial value[J]. Journal of Yanshan University, 2008, 32（2）: 173-175. (in Chinese)
    [12]
    董 杰, 李 欣, 方运海, 等. 基于改进模糊综合-指数平滑法的地下水水质评价和预测[J]. 中国海洋大学学报, 2020, 50(1): 126-135. (DONG J, LI X, FANG Y H, et al. Evaluation and prediction of groundwater quality based on improved fuzzy synthesis-exponential smoothing[J]. Periodical of Ocean University of China, 2020, 50(1): 126-135. (in Chinese)

    DONG J, LI X, FANG Y H, et al. Evaluation and prediction of groundwater quality based on improved fuzzy synthesis-exponential smoothing[J]. Periodical of Ocean University of China, 2020, 50（1）: 126-135. (in Chinese)
    [13]
    刘造保, 徐卫亚, 张开普, 等. 基于改进指数平滑法的岩体边坡变形预测[J]. 河海大学学报(自然科学版), 2009, 37(3): 313-316. (LIU Z B, XU W Y, ZHANG K P, et al. Prediction of rock slope deformation based on optimized exponential smoothing method[J]. Journal of Hohai University (Natural Sciences), 2009, 37(3): 313-316. (in Chinese)

    LIU Z B, XU W Y, ZHANG K P, et al. Prediction of rock slope deformation based on optimized exponential smoothing method[J]. Journal of Hohai University (Natural Sciences), 2009, 37（3）: 313-316. (in Chinese)
    [14]
    宋 芳, 张亚平, 张宗郁, 等. 基于遗传退火三次指数平滑的期货预测研究[J]. 计算机工程与设计, 2012, 33(5): 1963-1967. (SONG F, ZHANG Y P, ZHANG Z Y, et al. Futures forecasting with genetic/simulated annealing algorithm and cubic exponential smoothing[J]. Computer Engineering and Design, 2012, 33(5): 1963-1967. (in Chinese)

    SONG F, ZHANG Y P, ZHANG Z Y, et al. Futures forecasting with genetic/simulated annealing algorithm and cubic exponential smoothing[J]. Computer Engineering and Design, 2012, 33（5）: 1963-1967. (in Chinese)
    [15]
    高春雷, 安 泰, 向 兵, 等. 基于粒子群算法的指数平滑系数优化方法[J]. 西北大学学报(自然科学版), 2014, 44(3): 383-386. (GAO C L, AN T, XIANG B, et al. The exponential smoothing coefficient optimization method based on particle swarm algorithm[J]. Journal of Northwest University (Natural Science Edition), 2014, 44(3): 383-386. (in Chinese)

    GAO C L, AN T, XIANG B, et al. The exponential smoothing coefficient optimization method based on particle swarm algorithm[J]. Journal of Northwest University (Natural Science Edition), 2014, 44（3）: 383-386. (in Chinese)
    [16]
    LIU S G, SUN C Z, ZHOU H, et al. Intelligent prediction model (IPM) of foundation pit displacement based on extreme learning machine (ELM) and its application[J]. Processes, 2022, 10(5): 896. doi: 10.3390/pr10050896
    [17]
    MA Q W, LIU S H, FAN X Y, et al. A time series prediction model of foundation pit deformation based on empirical wavelet transform and NARX network[J]. Mathematics, 2020, 8(9): 1535. doi: 10.3390/math8091535
    [18]
    刘清龙, 吕颖慧, 秦 磊, 等. 基于改进最小二乘支持向量机组合模型的深基坑沉降变形预测[J]. 济南大学学报(自然科学版), 2024, 38(1): 8-14. (LIU Q L, LÜ Y H, QIN L, et al. Deep foundation pit settlement deformation prediction based on improved least square support vector machine combined model[J]. Journal of University of Jinan (Science and Technology), 2024, 38(1): 8-14. (in Chinese)

    LIU Q L, LÜ Y H, QIN L, et al. Deep foundation pit settlement deformation prediction based on improved least square support vector machine combined model[J]. Journal of University of Jinan (Science and Technology), 2024, 38（1）: 8-14. (in Chinese)
    [19]
    岳建伟, 仲豪磊, 赵丽敏, 等. 深基坑变形的滚动预测方法[J]. 中国科技论文, 2022, 17(6): 639-646. (YUE J W, ZHONG H L, ZHAO L M, et al. Rolling prediction method of deep foundation pit deformation[J]. China Sciencepaper, 2022, 17(6): 639-646. (in Chinese)

    YUE J W, ZHONG H L, ZHAO L M, et al. Rolling prediction method of deep foundation pit deformation[J]. China Sciencepaper, 2022, 17（6）: 639-646. (in Chinese)
    [20]
    曹 净, 丁文云, 赵党书, 等. 基于LSSVM-ARMA模型的基坑变形时间序列预测[J]. 岩土力学, 2014, 35(S2): 579-586. (CAO J, DING W Y, ZHAO D S, et al. Time series forecast of foundation pit deformation based on LSSVM-ARMA model[J]. Rock and Soil Mechanics, 2014, 35(S2): 579-586. (in Chinese)

    CAO J, DING W Y, ZHAO D S, et al. Time series forecast of foundation pit deformation based on LSSVM-ARMA model[J]. Rock and Soil Mechanics, 2014, 35（S2）: 579-586. (in Chinese)
    [21]
    马 琳. 基于ICEEMD-ICA准则进行数据处理的基坑变形组合预测研究[J]. 地质与勘探, 2023, 59(5): 1074-1082. (MA L. Combined prediction of foundation pit deformation based on ICEEMD-ICA criterion for data processing[J]. Geology and Exploration, 2023, 59(5): 1074-1082. (in Chinese)

    MA L. Combined prediction of foundation pit deformation based on ICEEMD-ICA criterion for data processing[J]. Geology and Exploration, 2023, 59（5）: 1074-1082. (in Chinese)
    [22]
    张生杰, 谭 勇. 基于LSTM算法的基坑变形预测[J]. 隧道建设(中英文), 2022, 42(1): 113-120. (ZHANG S J, TAN Y. Deformation prediction of foundation pit based on long short-term memory algorithm[J]. Tunnel Construction, 2022, 42(1): 113-120. (in Chinese)

    ZHANG S J, TAN Y. Deformation prediction of foundation pit based on long short-term memory algorithm[J]. Tunnel Construction, 2022, 42（1）: 113-120. (in Chinese)
    [23]
    钟正雄, 杨林德, 杨金松. 基坑变形的实时建模预报时序分析方法[J]. 工业建筑, 2000, 30(3): 1-3,42. (ZHONG Z X, YANG L D, YANG J S. Method of time series analysis of real-time modeling prediction for deep excavation deformation[J]. Industrial Construction, 2000, 30(3): 1-3,42. (in Chinese) doi: 10.3321/j.issn:1000-8993.2000.03.001

    ZHONG Z X, YANG L D, YANG J S. Method of time series analysis of real-time modeling prediction for deep excavation deformation[J]. Industrial Construction, 2000, 30（3）: 1-3,42. (in Chinese) doi: 10.3321/j.issn:1000-8993.2000.03.001
    [24]
    王 飞. 基坑变形组合预测分析及安全性评价[J]. 隧道建设(中英文), 2019, 39(2): 204-210. (WANG F. Combined prediction analysis and safety evaluation of foundation pit deformation[J]. Tunnel Construction, 2019, 39(2): 204-210. (in Chinese)

    WANG F. Combined prediction analysis and safety evaluation of foundation pit deformation[J]. Tunnel Construction, 2019, 39（2）: 204-210. (in Chinese)
    • Relative Articles
    • Supplements(0)
    • Cited By
  • 加载中

Catalog

    通讯作者: 陈斌, bchen63@163.com
    • 1. 

      沈阳化工大学材料科学与工程学院 沈阳 110142

    1. 本站搜索
    2. 百度学术搜索
    3. 万方数据库搜索
    4. CNKI搜索

    Figures(7)  / Tables(1)

    Get Citation
    PDF
    XML

    Article Metrics

    Article views (15) PDF downloads(5) Cited by()
    Proportional views
    Related

    Copyright © Geotechnical Engineering Technique京ICP备12043220号-2

    Address：No.79 Xibianmen Inner Street (Xibianmennei Dajie), Xicheng District, 100053, Beijing, P. R. China（100053）Tel：010-83117072 / 010-83196888Fax：（010）83117582Email：get099@263.net; ytgcjs@vip.163.com

    Supported by: Beijing Renhe Information Technology Co. Ltd    

    /

    DownLoad:  Full-Size Img  PowerPoint
    Return
    Return