A regression-based approach to the prediction of crest settlement of embankment dams under earthquake shaking

被引:16
|
作者
Javdanian, H. [1 ]
Sanayei, H. R. Zarif [1 ]
Shakarami, L. [1 ]
机构
[1] Shahrekord Univ, Dept Civil Engn, Shahrekord, Iran
关键词
Embankment dam; Earthquake; Crest settlement; Support vector regression; Predictive model; UNCONFINED COMPRESSIVE STRENGTH; DYNAMIC PROPERTIES; SCOUR DEPTH; DISPLACEMENTS; PARAMETERS; MODEL;
D O I
10.24200/sci.2018.50483.1716
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
The settlement of embankment dams is among the many major damages caused by earthquakes that, eventually, leads to dam instability. Therefore, an accurate assessment of the seismic settlement of embankment dams is of particular concern. This study aims to evaluate the settlement of embankment dams subjected to earthquake loads using regression-based methods. wide-ranging cases of real data on crest settlement of embankment dams caused by earthquakes were analyzed. Yield acceleration of dam (a(y)), maximum horizontal earthquake acceleration (a(max)), fundamental period of dam body (T-d), predominant period of earthquake (T-p), and earthquake magnitude (M-w) were considered as the most influential parameters that affect the seismic crest settlement of embankment dams. By applying Support Vector Regression (SVR) and Multiple Linear Regression (MLR) methods, two models were developed to estimate the earthquake-induced settlement of embankment dams. Subsequently, sensitivity analysis was conducted in order to assess the behavior of the proposed models under different conditions. Finally, the accuracy of the proposed models was compared with the existing relationship for the estimation of earthquake-induced crest settlement of embankment damns. Although both MLR- and SVR-based models enjoy acceptable accuracy in the estimation of the crest settlement of embankment dams under earthquake loading, the SVR-based model has higher accuracy. (C) 2020 Sharif University of Technology. All rights reserved.
引用
收藏
页码:671 / 681
页数:11
相关论文
共 50 条
  • [1] Prediction of earthquake-induced crest settlement of embankment dams using gene expression programming
    Seyrek, Evren
    Topcu, Sadettin
    GEOMECHANICS AND ENGINEERING, 2022, 31 (06) : 637 - 651
  • [2] A Regression-Based Approach to Scalability Prediction
    Barnes, Bradley J.
    Rountree, Barry
    Lowenthal, David K.
    Reeves, Jaxk
    de Supinski, Bronis
    Schulz, Martin
    ICS'08: PROCEEDINGS OF THE 2008 ACM INTERNATIONAL CONFERENCE ON SUPERCOMPUTING, 2008, : 368 - +
  • [3] Modeling and prediction of earthquake-related settlement in embankment dams using non-linear tools
    Zeroual, Abdelatif
    Fourar, Ali
    Merrouchi, Farida
    Seghir, Tarek
    Berghout, Mourad
    Kerkouri, Ali
    MODELING EARTH SYSTEMS AND ENVIRONMENT, 2022, 8 (02) : 1949 - 1962
  • [4] Modeling and prediction of earthquake-related settlement in embankment dams using non-linear tools
    Abdelatif Zeroual
    Ali Fourar
    Farida Merrouchi
    Tarek Seghir
    Mourad Berghout
    Ali Kerkouri
    Modeling Earth Systems and Environment, 2022, 8 : 1949 - 1962
  • [5] Seismic damage prediction of rockfill dams based on crest settlement and missing data imputation
    Zheng, Zhou
    Li, Yanlong
    Zhang, Ye
    Wen, Lifeng
    Wang, Ting
    She, Lei
    Yang, Tao
    ENGINEERING STRUCTURES, 2025, 330
  • [6] Support vector regression-based model for prediction of behavior stone column parameters in soft clay under highway embankment
    Qasim A. Aljanabi
    Zamri Chik
    Mohammed Falah Allawi
    Amr H. El-Shafie
    Ali N. Ahmed
    Ahmed El-Shafie
    Neural Computing and Applications, 2018, 30 : 2459 - 2469
  • [7] Support vector regression-based model for prediction of behavior stone column parameters in soft clay under highway embankment
    Aljanabi, Qasim A.
    Chik, Zamri
    Allawi, Mohammed Falah
    El-Shafie, Amr H.
    Ahmed, Ali N.
    El-Shafie, Ahmed
    NEURAL COMPUTING & APPLICATIONS, 2018, 30 (08): : 2459 - 2469
  • [8] Prediction of Sea Level Oscillations: Comparison of Regression-based Approach
    Jamali, Ahmad Fitri
    Iaeng, Aida Mustapha Member
    Mostafa, Salama A.
    ENGINEERING LETTERS, 2021, 29 (03) : 990 - 995
  • [9] Prediction and sensitivity analysis of embankment dam settlement under earthquake loading using gene expression programming
    Fahimi, Reza
    Seyedkazemi, Ali
    Kutanaei, Saman Soleimani
    GEOMECHANICS AND GEOENGINEERING-AN INTERNATIONAL JOURNAL, 2025, 20 (01): : 115 - 137
  • [10] A regression-based machine learning approach for the prediction of lung function decline
    Poulou, Angeliki
    Poulos, Marios
    Panas, Maximilianos
    2022 12TH INTERNATIONAL CONFERENCE ON DEPENDABLE SYSTEMS, SERVICES AND TECHNOLOGIES (DESSERT), 2022,