Gas Disaster Prediction Method Research Based On Information Fusion

Coal and gas outburst is a disaster which has a biggest danger,and a largest damage.Nowadays,the coal companies have put the prevention and controlling of coal and gas outburst as a most important task.Coal and gas outburst is a complex dynamic phenomena, it is the result of many factors which have a complex relationship with the outburst,so that it is difficult to analysis it by using some simple mathematical model.It is a vital topic for us to build a model that can analysis the weights of factors and make a accurate prediction of the coal and gas outburst at the same time.In this paper, a number of guess to explain the reasons for the outburst is introduced to discuss the objective factors and man-made causes of the coal and gas outburst.On this basis,some predicting methods been used is studied to analyze the advantages and disadvantages.On the basis of the studies of traditional forecasting models and predicting methods, the paper blur multi-sensor data fusion technology into the study of coal mine gas outburst prediction. Firstly,Using a Improved AHP analysis to discuss the weights of influencing factors;secondly, using fuzzy probability and application of improved statistical methods to solving decision matrix factors set;finally, on the right to get the weight vector and decision matrix fusion operation, a final decision result can be obtained. The biggest advantage of this design is to reduce the impact of a single sensor failure to the result,so that the system has a strong viability and a higher degree of confidence.In front of the contents,a prediction model of fuzzy data fusion construct is contributed to analyze the coal and gas outburst,then some historical data records of a coal company in Shanxi is used to validate the model.the result shows that the model improves the performance and stability of early warning systems.