About this document
Soil Classification via Random Forests by Juan Brugada is a document available to read on EtoBox.
This document summarizes a study that used random forests (RF), a machine learning algorithm, to classify soil conditions encountered during tunnel boring machine (TBM) excavation based on continuous TBM sensor data. The study used data from a TBM project in Seattle, Washington to classify soil into different engineering soil units (ESUs). RF was able to accurately classify soil conditions and identify transitions between soil types based on feature importance measures. While some TBM sensor readings were m
- Author
- Juan Brugada
- Language
- EN