Optimized kernel extreme learning machine using Sine Cosine Algorithm for prediction of unconfined compression strength of MICP cemented soil
Author:
Funder
National Natural Science Foundation of China
Natural Science Foundation of Hunan Province
Publisher
Springer Science and Business Media LLC
Link
https://link.springer.com/content/pdf/10.1007/s11356-024-32687-2.pdf
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3. Ahenkorah I, Rahman MM, Karim MR, Teasdale PR (2020) A comparison of mechanical responses for microbial and enzyme-induced cemented sand. Géotech Lett 10(4):1–26
4. Ahenkorah I, Rahman MM, Karim MR, Beecham S (2023) Unconfined compressive strength of MICP and EICP treated sands subjected to cycles of wetting-drying, freezing-thawing and elevated temperature: experimental and EPR modelling. J Rock Mech Geotech 15:1226–1247. https://doi.org/10.1016/j.jrmge.2022.08.007
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1. Advancing earth science in geotechnical engineering: A data-driven soft computing technique for unconfined compressive strength prediction in soft soil;Journal of Earth System Science;2024-08-17
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