Classification of Rockburst in Underground Projects: Comparison of Ten Supervised Learning Methods-Reference-Cited by-同舟云学术

Classification of Rockburst in Underground Projects: Comparison of Ten Supervised Learning Methods

Published:2016-09 Issue:5 Volume:30 Page:04016003
ISSN:0887-3801
Container-title:Journal of Computing in Civil Engineering
language:en
Short-container-title:J. Comput. Civ. Eng.

Author:

Zhou Jian¹,Li Xibing²,Mitri Hani S.³

Affiliation:

1. School of Resources and Safety Engineering, Central South Univ., #932 Lushan South Rd., Changsha 410083, China; Visiting Scholar, Dept. of Mining and Materials Engineering, McGill Univ., 3450 University St., Montreal, QC, Canada H3A 0E8 (corresponding author).

2. Professor, School of Resources and Safety Engineering, Central South Univ., #932 Lushan South Rd., Changsha 410083, China.

3. Professor, Dept. of Mining and Materials Engineering, McGill Univ., 3450 University St., Montreal, QC, Canada H3A 0E8.

Publisher

American Society of Civil Engineers (ASCE)

Subject

Computer Science Applications,Civil and Structural Engineering

Link

http://ascelibrary.org/doi/pdf/10.1061/%28ASCE%29CP.1943-5487.0000553

Reference156 articles.

1. Knowledge-based and data-driven fuzzy modeling for rockburst prediction

2. Predicting the Outcome of Construction Litigation Using Boosted Decision Trees

3. Predicting the Outcome of Construction Litigation Using an Integrated Artificial Intelligence Model