Logistic Regression Model for Evaluating Soil Liquefaction Probability Using CPT Data-Reference-Cited by-同舟云学术

Logistic Regression Model for Evaluating Soil Liquefaction Probability Using CPT Data

Published:2006-06 Issue:6 Volume:132 Page:694-704
ISSN:1090-0241
Container-title:Journal of Geotechnical and Geoenvironmental Engineering
language:en
Short-container-title:J. Geotech. Geoenviron. Eng.

Author:

Lai Sheng-Yao¹²³,Chang Wen-Jong¹²³,Lin Ping-Sien¹²³

Affiliation:

1. Researcher, Harbor and Marine Technology Center, Institute of Transportation, Wuchi, Taichung County, Taiwan (corresponding author).

2. Assistant Professor, Dept. of Civil Engineering, National Chi Nan Univ., Puli, Nantou, Taiwan.

3. Professor, Dept. of Civil Engineering, National Chung-Hsing Univ., Taichung, Taiwan.

Publisher

American Society of Civil Engineers (ASCE)

Subject

Geotechnical Engineering and Engineering Geology,General Environmental Science

Link

http://ascelibrary.org/doi/pdf/10.1061/%28ASCE%291090-0241%282006%29132%3A6%28694%29

Reference31 articles.

1. Boulanger R. W. and Idriss I. M. (2004). “State normalization of penetration resistance and the effect of overburden stress on liquefaction resistance.” Proc. 11th SDEE and 3rd ICEGE Conf. Berkeley Calif. 484–491.

2. Statistics of liquefaction and SPT results;Christian J. T.;J. Geotech. Eng. Div., Am. Soc. Civ. Eng.,1975

3. Garson D. (2003). “Logistic regression.” ⟨http://www2.chass.ncsu.edu/garson/pa765/logistic.htm⟩

Cited by 45 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Utilizing Machine Learning for Cone Penetration Test-Based Soil Classification;Transportation Research Record: Journal of the Transportation Research Board;2024-05-16

2. On application of machine learning classifiers in evaluating liquefaction potential of civil infrastructure;Interpretable Machine Learning for the Analysis, Design, Assessment, and Informed Decision Making for Civil Infrastructure;2024

3. Performance-Based Liquefaction Analysis and Probabilistic Liquefaction Hazard Mapping Using Cpt Data within the Fraser River Delta, Canada;2024

4. Probabilistic Liquefaction Assessment Based on an In-situ State Parameter Considering Soil Spatial Variability and Various Uncertainties;KSCE Journal of Civil Engineering;2023-08-11

5. Liquefaction Potential Assessment of Soils Using Machine Learning Techniques: A State-of-the-Art Review from 1994–2021;International Journal of Geomechanics;2023-07