Research Project at National Institute for Research in Digital Science and Technology (INRIA Grand Est) and Elie Cartan Institute of Lorraine (IECL). The project endeavors to leverage machine learning methods to address challenges related to rock fragmentation.
In this repository, you will come across a Jupyter notebook that provides a comprehensive summary of the machine learning code I utilized in a fragmentation example. The specific example pertains to determining the median size of rock fragments following a blast. Additionally, there is a PDF file included in the repository that spans about 50 pages. This PDF delves into the fragmentation problem, introduces fundamental concepts of machine learning, explores data handling techniques, and outlines the various models I employed. Moreover, it thoroughly explains the machine learning approach I adopted and presents the results I obtained.
All documents are in French.
You can also refer to the HAL page this project: https://inria.hal.science/hal-04142294
Victor Hoffmann.
Madalina Deaconu (INRIA & IECL) and Antoine Lejay (INRIA & IECL).