Research on machine learning based rockburst intensity prediction model

• Main Author: Mu, Xinyi
• Other Authors: Su Rong
• Format: Thesis-Master by Coursework
• Language: English
• Published: Nanyang Technological University 2022
• Subjects: Engineering::Electrical and electronic engineering
• Online Access: https://hdl.handle.net/10356/157178
• Institution: Nanyang Technological University

Rockburst is one of the difficult problems in large underground geotechnical and deep resource extraction projects, and accurate prediction of rockburst intensity level has important engineering significance and academic value. However, traditional prediction models are affected by a variety of complex factors, and their effectiveness needs to be improved in terms of index weight determination and practical engineering applications. In this dissertation, based on the established rockburst intensity level prediction database, two types of rockburst intensity level prediction models are established using machine learning techniques, and the effectiveness of the prediction models is verified.