Coal mine driving working face air volume demand prediction method based on support vector machine

The invention discloses a coal mine driving working face air volume demand prediction method based on a support vector machine, which is characterized by comprising the following steps of: establishing and predicting a VM (virtual machine) model by taking gas concentration test data of a coal mine driving working face as a training sample and compiling a Matlab calculation program. The method can be used for predicting the ventilation demand of the driving face. The problem that due to the fact that various harmful gases, dust, temperature and the like of the driving working face have randomness and uncertainty, the actual production requirement cannot be met is solved, the ventilation effect of the roadway driving working face is improved, consumption of electric power resources is reduced, and the safety of a coal mine is improved. The method has the advantages of good practical application value, reasonable design, high practicability and high popularization and application value. 本发明公开了一种基于支持向量机的煤矿掘进工作面风量