DOI: 10.1007/s11069-021-04594-z
论文题名: The adoption of ELM to the prediction of soil liquefaction based on CPT
作者: Zhang Y.-G. ; Qiu J. ; Zhang Y. ; Wei Y.
刊名: Natural Hazards
ISSN: 0921030X
出版年: 2021
卷: 107, 期: 1 起始页码: 539
结束页码: 549
语种: 英语
中文关键词: Cone penetration test
; Extreme learning machine
; Prediction model
; Soil liquefaction
英文关键词: accuracy assessment
; computer simulation
; cone penetration test
; dynamic response
; liquefaction
; nonlinearity
; numerical model
; prediction
; seismic response
; soil mechanics
英文摘要: Establishing a soil liquefaction prediction model with high accuracy is a critical way to evaluate the quality of in situ and prevent the loss caused by seismic. In this paper, considering the advantage of cone penetration test (CPT) over standard penetration test (SPT) and the suitability for dealing with the nonlinear problems of the extreme learning machine (ELM), the ELM was tried to train the prediction model. Firstly, seven prediction parameters were analyzed and determined; then 226 CPT samples were divided into the training set and test set; then the parameter of ELM model was assured by comparing the training accuracy and speed of model when setting the number of the neuron of the hidden layer from 5 to 16 and the activation function as sig , sin , hardlim. Finally, the performance of the established ELM model was tested through the test set. The results showed the accuracy of using function sin was 81.43% and 87.50% for the training set and test set, respectively; at the same time, the operation was 1.5055 s which was not much different from other two functions. The prediction model based on CPT perform better than that of SPT and can obtain a highly accurate prediction of 100% for the liquefied case and overall accuracy of 87.5%. ELM was proved to be feasible to be used and developed into the in situ evaluation. © 2021, The Author(s), under exclusive licence to Springer Nature B.V. part of Springer Nature. Citation statistics:
资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/169517
Appears in Collections: 气候变化与战略
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作者单位: Key Laboratory of Geotechnical and Underground Engineering of Ministry of Education, and Department of Geotechnical Engineering, Tongji University, Shanghai, 200092, China; College of Civil Engineering, University of Science and Technology Liaoning, Anshan, 114053, China; College of Civil and Transportation Engineering, Hohai University, Nanjing, 210098, China; Geological Survey of Jiangsu Province, Nanjing, 210049, China
Recommended Citation:
Zhang Y.-G.,Qiu J.,Zhang Y.,et al. The adoption of ELM to the prediction of soil liquefaction based on CPT[J]. Natural Hazards,2021-01-01,107(1)