Long-term prediction of rockburst hazard in deep underground openings using three robust data mining techniques

Title
Long-term prediction of rockburst hazard in deep underground openings using three robust data mining techniques
Authors
Keywords
Rockburst occurrence, Data mining techniques, Emotional neural network, Gene expression programming, C4.5 algorithm, Conventional criteria
Journal
ENGINEERING WITH COMPUTERS
Volume -, Issue -, Pages -
Publisher
Springer Nature
Online
2018-06-16
DOI
10.1007/s00366-018-0624-4

Ask authors/readers for more resources

Reprint

Contact the author

Find the ideal target journal for your manuscript

Explore over 38,000 international journals covering a vast array of academic fields.

Search

Become a Peeref-certified reviewer

The Peeref Institute provides free reviewer training that teaches the core competencies of the academic peer review process.

Get Started