Research on gas emission quantity prediction model based on EDA-IGA

• DOI: 10.1016/j.heliyon.2023.e17624
• Publication Date: 2023-06-25T02:31:01Z
• Authors: Peng Ji; Shiliang Shi; Xingyu Shi
• Keywords: Immune genetic algorithm; Social sciences (General); H1-99; Q1-390; Science (General); Estimation of distribution algorithm; Gas emission quantity; Prediction; Research Article

In order to accurately predict the possible gas emission quantity in coal mines, it is proposed use multi-thread calculation of Immune Genetic Algorithm (IGA) and injection vaccines improve accuracy prediction combine Estimation Distribution (EDA) distribution probability excellent populations. Calculating, selecting populations for iteration, optimize population generation process Algorithm, so that quality continuously optimized improved, optimal solution obtained, thereby establishing a model based on Algorithm. Using 9136 mining face with hazards mine from Shandong Province China as object, absolute used scale quantity, found can which consistent on-site unanimous. comparison IGA, results has increased by 9.51%, number iterations achieve required goal been reduced 67%, indicating EDA better role optimizing update such genetic selection IGA. Comparing other models, EDA-IGA 94.93%, highest accuracy, this be new method emission. Accurately predicting provide guidance safe mines. The also safety indicator reduce possibility accidents, ensure personal miners economic losses