A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2019; you can also visit the original URL.
The file type is application/pdf
.
A novel prediction model for the degree of rescue safety in mine thermal dynamic disasters based on fuzzy analytical hierarchy process and extreme learning machine
2018
International Journal of Heat and Technology
Considering the rapid development, uncertain situations and prediction difficulty of mine thermal dynamic disasters (MTDDs), this paper combines the fuzzy analytical hierarchy process (FAHP) and extreme learning machine (ELM) into a prediction model to quantify the degree of MTDD rescue safety in a fast and accurate manner. Firstly, a static FAHP model was constructed by the Delphi, AHP, and fuzzy comprehensive evaluation (FCE) to assess various MTDD rescue cases, quantify the exact degree of
doi:10.18280/ijht.360424
fatcat:xbes3zg4rbbtrpdiz32voyg6z4