Title: Study on the improvement of the genetic algorithm for prediction of coal and gas outburst risk

Authors: Ji Nan; Peng Yamian; Wang Xinchun

Addresses: College of Science, North China University of Science and Technology, 063009, China ' College of Science, North China University of Science and Technology, 063009, China ' College of Science, North China University of Science and Technology, 063009, China

Abstract: Coal and gas outburst is a very complex phenomenon of dynamic disaster in coal mine, where exists a complex non-linear mapping relationship which could not be described with functions between outburst risk and its influential factors. In this paper, from operator theory, the choice of initial parameters is optimised, and genetic algorithm is improved. Mathematical model of coal and gas outburst risk prediction is established, and the improved genetic algorithm was applied to the risk prediction model.

Keywords: coal and gas outburst risk; genetic algorithms; risk prediction; genetic operations; fitness function; penalty function; coal mines; coal mining; mathematical modelling.

DOI: 10.1504/IJAMC.2016.080978

International Journal of Advanced Media and Communication, 2016 Vol.6 No.2/3/4, pp.122 - 131

Received: 26 Feb 2016
Accepted: 18 May 2016

Published online: 10 Dec 2016 *

Full-text access for editors Access for subscribers Purchase this article Comment on this article