煤矿安全2024，Vol.55Issue(6)：184-191,8.DOI:10.13347/j.cnki.mkaq.20231361
基于PCA-GA-RF的矿井突水水源快速识别模型
Mine water inrush source identification model based on PCA-GA-RF
摘要
Abstract
Mine sudden water has become one of the main hazards affecting the safety production of mines,and rapid and accurate identification of the type of sudden water source is a key step in the management of mine sudden water disaster,so a PCA-GA-RF-based mine sudden water source identification model is proposed.Based on the measured data of 88 groups of water samples from Xieqiao Coal Mine in Yingshang County,Anhui Province,and following the principle of stratified random sampling,it was divided into 62 groups of training samples and 26 groups of prediction samples according to the ratio of 7:3,and the four principal compon-ents were extracted by PCA to construct the PCA-GA-RF model,and compare it with the PCA-RF,PCA-ABC-RF and PCA-FA-RF models.The results show that the PCA-GA-RF model discriminates the results with an accuracy of 96.1538%,which is superior with the highest accuracy,precision,recall and F1 value compared with other models.关键词
矿井突水/水源识别/主成分分析(PCA)/随机森林(RF)/遗传算法(GA)Key words
mine water inrush/water source identification/principal component analysis(PCA)/random forest(RF)/genetic al-gorithm(GA)分类
矿业与冶金引用本文复制引用
肖观红,鲁海峰..基于PCA-GA-RF的矿井突水水源快速识别模型[J].煤矿安全,2024,55(6):184-191,8.基金项目
国家自然科学基金资助项目(41977253) （41977253）
安徽理工大学研究生创新基金资助项目(2023cx2007) （2023cx2007）
