Estimating shear wave velocity of soil deposits using polynomial neural networks: Application to liquefaction

被引:24
|
作者
Ghorbani, Ali [1 ]
Jafarian, Yaser [2 ]
Maghsoudi, Mohammad S. [1 ]
机构
[1] Guilan Univ, Fac Engn, Rasht, Iran
[2] Semnan Univ, Dept Civil Engn, Semnan, Iran
关键词
Shear wave velocity; In-situ tests; PNN; Standard penetration test; Database; Liquefaction; RESISTANCE; MODEL;
D O I
10.1016/j.cageo.2012.03.002
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
Geophysical and geotechnical field investigations have introduced several techniques to measure in-situ shear wave velocity of soils. However, there are some difficulties for the easy and economical use of these techniques in the routine geotechnical engineering works. For the soil deposits, researchers have developed correlations between shear wave velocity and SPT-N values. In the present study, a new database containing the measured shear wave velocity of soil deposits have been compiled from the previously published studies. Using polynomial neural network (PNN), a new correlation has been subsequently developed for the prediction of shear wave velocity. The developed relationship shows an acceptable performance compared with the available relationships. Three examples are then presented to confirm accuracy and applicability of the proposed equation in the field of liquefaction potential assessment. (C) 2012 Elsevier Ltd. All rights reserved.
引用
收藏
页码:86 / 94
页数:9
相关论文
共 50 条
  • [1] Soil liquefaction evaluation using shear wave velocity
    Kayabali, K
    [J]. ENGINEERING GEOLOGY, 1996, 44 (1-4) : 121 - 127
  • [2] Shear Wave Velocity by Polynomial Neural Networks and Genetic Algorithms Based on Geotechnical Soil Properties
    Mola-Abasi, H.
    Eslami, A.
    Shourijeh, P. Tabatabaie
    [J]. ARABIAN JOURNAL FOR SCIENCE AND ENGINEERING, 2013, 38 (04) : 829 - 838
  • [3] Shear Wave Velocity by Polynomial Neural Networks and Genetic Algorithms Based on Geotechnical Soil Properties
    H. Mola-Abasi
    A. Eslami
    P. Tabatabaie Shourijeh
    [J]. Arabian Journal for Science and Engineering, 2013, 38 : 829 - 838
  • [4] Evaluation of liquefaction potential of soil deposits using artificial neural networks
    Hanna, Adel M.
    Ural, Derin
    Saygili, Gokhan
    [J]. ENGINEERING COMPUTATIONS, 2007, 24 (1-2) : 5 - 16
  • [5] Liquefaction Analysis using Shear Wave Velocity
    Kamel, Filali
    Badreddine, Sbartai
    [J]. CIVIL ENGINEERING JOURNAL-TEHRAN, 2020, 6 (10): : 1944 - 1955
  • [6] Evaluation of liquefaction potential of soil using the shear wave velocity in Tehran, Iran
    Rahmanian, Sahar
    Rezaie, Fereydoun
    [J]. GEOSCIENCES JOURNAL, 2017, 21 (01) : 81 - 92
  • [7] Evaluation of liquefaction potential of soil using the shear wave velocity in Tehran, Iran
    Sahar Rahmanian
    Fereydoun Rezaie
    [J]. Geosciences Journal, 2017, 21 : 81 - 92
  • [8] Shear wave velocity and soil type microzonation using neural networks and geographic information system
    Nejad, Mohammad Motalleb
    Momeni, Mohammad Sadegh
    Manahiloh, Kalehiwot Nega
    [J]. SOIL DYNAMICS AND EARTHQUAKE ENGINEERING, 2018, 104 : 54 - 63
  • [9] The adoption of deep neural network (DNN) to the prediction of soil liquefaction based on shear wave velocity
    Zhang, Yonggang
    Xie, Yuanlun
    Zhang, Yan
    Qiu, Junbo
    Wu, Sunxin
    [J]. BULLETIN OF ENGINEERING GEOLOGY AND THE ENVIRONMENT, 2021, 80 (06) : 5053 - 5060
  • [10] The adoption of deep neural network (DNN) to the prediction of soil liquefaction based on shear wave velocity
    Yonggang Zhang
    Yuanlun Xie
    Yan Zhang
    Junbo Qiu
    Sunxin Wu
    [J]. Bulletin of Engineering Geology and the Environment, 2021, 80 : 5053 - 5060