Hazard prediction of coal and gas outburst based on the Hamming distance artificial intelligence algorithm (HDAIA)

作     者：Peng Ji Shiliang Shi 

作者机构：College of Resource Environment and Safety EngineeringHunan University of Science and TechnologyXiangtan411201China Provincial Key Laboratoryof Safe Mining Technques of Coal MinesHunan Universityof Science and TechnoogyTaoyuan Road Yuhu District Xiangtan4112 China 

出 版 物：《Journal of Safety Science and Resilience》 (安全科学与韧性（英文）)

年 卷 期：2023年第4卷第2期

页      面：151-158页

核心收录：

学科分类：1004[医学-公共卫生与预防医学(可授医学、理学学位)] 08[工学] 081104[工学-模式识别与智能系统] 0811[工学-控制科学与工程] 

基　　金：supported by the National Natural Science Foundation of China(Nos.51974120 and 52274196)。 

主　　题：Coal and gas outburst Hammingdistance Artificial immune algorithm Risk prediction 

摘      要：Currently,coal mining faces the uncertainty of the risk of coal and gas outbursts and inaccurate prediction results.Owing to this,an artificial immune algorithm(AIA)was developed for coal and gas outburst prediction based on the Hamming distance(HD)calculation method of antibody and antigen affinity called the Hamming distance artificial intelligence algorithm(HDAIA).The correlation matrix of coal and gas outburst indicators was constructed using the interpolation function in the algorithm.The HD algorithm was used to obtain the affinity between the antibody and antigen,and the minimum HD was screened to obtain the prediction result.The collected dynamic data of the drilling cuttings gas desorption index Ki and the drilling cuttings weight S during the excavation process of the 11,192-working face of a coal mine in Guizhou Province,China,were used as prediction indices.The results indicate that the prediction result of the HDAIA for the risk of coal and gas outbursts is consistent with the actual risk of outbursts,and it has a good prediction of the risk of coal and gas outbursts.The HDAIA can be used as a novel method for predicting the risk of coal and gas outbursts.