The classification of surrounding rock stability of coal roadway has important theoretical and practical significance for the design, construction and management of on-site rock mass engineering.This paper selected seven key indexes that affect the surrounding rock stability of coal roadway, collected the samples through field cases collection, questionnaires and literature measurement, and established the surrounding rock stability classification database.By drawing on six machine learning methods, this study established the classification prediction models of surrounding rock stability of coal roadway accordingly.Through model calculation, it is concluded that the Neural Network and the improved Support Vector Machine model have higher prediction accuracy.The model is applied to the actual project of Huozhou mining area.Results show that the neural network and the improved support vector machine methods have high prediction accuracy and good reliability.
