Prediction model of coal and gas outburst based on quantum genetic fuzzy inference system
GUO Jindong
Abstract：A prediction method based on adaptive neuro-fuzzy inference system and improved real-coded quantum genetic algorithm is proposed to improve accuracy of coal and gas outburst dangerous level.The fuzzy rules of ANFIS is extracted directly from sample data by data-driven method,and an adaptive neuro-fuzzy in-ference system for coal and gas outburst prediction is established.In view of the low accuracy of ANFIS pre-diction and the large number of parameters of fuzzy reasoning system,an improved quantum genetic algorithm is used to train adaptive neuro-fuzzy inference system.The Archimedes spiral space search mechanism of the bald eagle search algorithm is introduced into real-coded quantum genetic algorithm to update individual,and the differential mutation mechanism is mutate the worst individual to maintain the diversity of the population,and Gauss-Cauchy mutation is used to alternate the optimal individuals to help them escape from the local ex-tremum region quickly and accelerate the iteration speed of the algorithm.The different forecast methods are conducted on typical engineering practical data of coal and gas outburst.The results show that IRQGA can yield a superior optimization performance to other algorithm,and the prediction accuracy of the IRQGA-ANFIS method is 94.44%,and the MAEs in 30 rounds of independent operation of the model built in this paper re-duce by 0.0245,0.1184 on average,and the MSEs reduce by 0.0162,0.1849 on average,and the RMSEs re-duce by 0.0172,0.1721.The model built in this paper has better forecast ability and more accuracy for pre-dicting the outburst fatalness.
Keywords：coal and gas outburstpredictionANFISreal-coded quantum genetic algorithmArchimedes spiral space search mechanismGauss-Cauchy mutation
Publication Date：2023-12-28
Online Publishing Date：2025-08-15(First online date of this platform, not the publication date of the document)
Pages：8( 30-37 )