Case Study on Analysis of Soil Compression Index Prediction Performance Using Linear and Regularized Linear Machine Learning Models (In Korea)

Case Study on Analysis of Soil Compression Index Prediction Performance Using Linear and Regularized Linear Machine Learning Models (In Korea)

The compression index (C<sub>c</sub>) is a critical soil parameter that is used to estimate the consolidation settlement of ground. In this study, the compression index, typically obtained through consolidation tests, was predicted using machine learning techniques after preprocessing da...

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Bibliographic Details
Main Authors: Seungyeon Ryu, Jin Kim, Hyoyeop Choi, Jongyoung Lee, Junggeun Han
Format: Article
Language:English
Published: MDPI AG 2025-03-01
Series:Applied Sciences
Subjects:
machine learning
soft ground
compression index
Saemangeum reclaimed tidal land
bedrock
Online Access:https://www.mdpi.com/2076-3417/15/5/2757
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