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Strength Prediction by Support Vector Regression (SVR) for Biopolymer-Based Soil Treatment (BPST)
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Publication Year
2023-01-01
Journal
Geotechnical Special Publication
Publisher
American Society of Civil Engineers (ASCE)
Citation
Geotechnical Special Publication, Vol.2023-March No.GSP 342, pp.281-286
Mesh Keyword
Biological soilGround improvementImprovement methodsLow carbonPore cloggingSoil treatmentsStrength predictionSupport vector regressionsTreatment methodsUnconfined compressive strength
All Science Classification Codes (ASJC)
Civil and Structural EngineeringArchitectureBuilding and ConstructionGeotechnical Engineering and Engineering Geology
Abstract
For sustainable and environmentally friendly geotechnical engineering, biological soil treatment methods have recently been actively introduced. Biopolymer-based soil treatment (BPST) is regarded as a low carbon footprint ground improvement method with adequate strengthening and pore clogging characteristics. However, no detailed analysis of the relationship between the components that have a significant impact on BPST strengthening behavior has been carried out. Because BPST is frequently implemented as a mixture of soil, biopolymer, and water, different results can be obtained depending on the hydrogel phase and soil type. Using unconfined compressive strength (UCS) data for BPST obtained from laboratory test, support vector regression (SVR) was used in this study to predict the UCS and examine the dominant characteristics influencing the strengthening behavior of biopolymer-treated soil mixes.
ISSN
0895-0563
Language
eng
URI
https://aurora.ajou.ac.kr/handle/2018.oak/36917
https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85151632403&origin=inward
DOI
https://doi.org/10.1061/9780784484692.029
Journal URL
http://ascelibrary.org/
Type
Conference
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Chang, Il Han Image
Chang, Il Han장일한
Department of Civil Systems Engineering
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