In order to solve the problems of non-linear

time-varying and multi-parameter strong coupling of coal mine gas monitoring system

a coal mine safety monitoring strategy based on differential evolution improved bat algorithm（ DEBA） optimized weighted D-S evidence fusion was proposed. The primary data collected by various sensors in coal mines is processed through kernel independent principal component analysis（ KICA） algorithm to extract features. Then weighted DS evidence theory is used for data fusion processing. At the same time

DEBA algorithm is used to optimize the weights of weighted D-S theory. The establishment of a coal mine gas monitoring model can make timely judgments on the state of gas under the mine and take corresponding decisions. The simulation results of Matlab show that the monitoring model can significantly improve the accuracy and generalization ability of coal mine gas monitoring and the rapidity and rationality of global decision making.