Plasticity-Based Liquefaction Prediction Using Support Vector Machine and Adaptive Neuro-Fuzzy Inference System-Reference-Cited by-同舟云学术

Plasticity-Based Liquefaction Prediction Using Support Vector Machine and Adaptive Neuro-Fuzzy Inference System

Published:2023 Issue: Volume: Page:515-527
ISSN:2366-2557
Container-title:Lecture Notes in Civil Engineering
language:
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Author:

Ghani Sufyan,Kumari Sunita

Publisher

Springer Nature Singapore

Link

https://link.springer.com/content/pdf/10.1007/978-981-19-6998-0_44

Reference27 articles.

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2. Bray JD, Sancio RB, Riemer MF, Durgunoglu T (2004) Liquefaction susceptibility of fine-grained soils. In: Proceedings of the 11th international conference on soil dynamics and earthquake engineering and 3d international conference on earthquake geotechnical engineering, pp 655–662

3. Bray JD, Sancio RB (2006) Assessment of the liquefaction susceptibility of fine-grained soils. J Geotech Geoenviron Eng 132(9):1165–1177. https://doi.org/10.1061/(ASCE)1090-0241(2006)132:9(1165)

4. Ghani S, Kumari S (2021) Insight into the effect of fine content on liquefaction behavior of soil. Geotech Geol Eng 39(1):1–12. https://doi.org/10.1007/s10706-020-01491-3

5. Ghani S, Kumari S (2021b). Liquefaction susceptibility of high seismic region of Bihar considering fine content. In: Basics of computational geophysics, pp 105–120. https://doi.org/10.1016/b978-0-12-820513-6.00012-6

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