RBF neural network risk monitoring and early warning model of mine ventilation system based on cooperative game method
In the production process of coal mine,mine ventilation system plays an important role in mine safety production.In order to ensure the safety of mine ventilation system and achieve real-time monitoring,it is necessary to identify and estimate the risks of the mine ventilation system.The traditional BP neural network evaluation method has low accuracy,a BPF risk early warning model based on cooperative game method was proposed.Firstly,the safety risk index system of mine ventilation system was established,and the weight of each index was calculated by cooperative game theory,and its importance was ranked.Finally,RBF neural network was used to evaluate and predict the safety risk.Taking the mine ventilation system of Baode Coal Mine as an example,the real-time simulation and dynamic early warning analysis of mine ventilation were carried out.The simulation experiment results show that the method has a cer-tain accuracy and effectiveness,and provides a technical means for grasping the mine ventilation safety situation in real time.
analytic hierarchy processRBF neural networkcooperative game methodmine ventilationsafety evaluation
万方数据
维普
