Predicting the Young’s modulus of rock material based on petrographic and rock index tests using boosting and bagging intelligence techniques

• Main Authors: Long, Tsang, Biao, He, A. Rashid, Ahmad Safuan, Jalil, Abduladheem Turki, Sabri, Mohanad Muayad
• Format: Article
• Language: English
• Published: MDPI 2022
• Subjects: TA Engineering (General). Civil engineering (General)
• Online Access: http://eprints.utm.my/id/eprint/100982/1/AhmadSafuan2022_PredictingtheYoungsModulusofRockMaterial.pdf; http://eprints.utm.my/id/eprint/100982/; http://dx.doi.org/10.3390/app122010258
• Institution: Universiti Teknologi Malaysia

Rock deformation is considered one of the essential rock properties used in designing and constructing rock-based structures, such as tunnels and slopes. This study applied two well-established ensemble techniques, including boosting and bagging, to the artificial neural networks and decision tree m...