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Machine Learning Techniques For Cohesive Soil Classification in Construction in Vietnam by lvlovot is a document available to read on EtoBox.

This study explores the application of machine learning techniques, specifically K-Nearest Neighbors (KNN) and Support Vector Machine (SVM), for the classification of cohesive soils in construction projects in Vietnam. Analyzing 5,869 soil samples from 39 projects, the research demonstrates that machine learning can significantly enhance the accuracy and efficiency of soil classification compared to traditional methods. The findings highlight the importance of integrating advanced algorithms into geotechnic

Author

lvlovot

Language

EN