Gas Emission Assessment System Association Rules Algorithm Applied Research

The gas is one of the most important factors which endanger the security of the mining production. The gas hazard is one of the most serious hazards. The local of the range of the mining exploit from which the gas emit is named the origin of the gas. The number of the origin of the gas emission and the amount of the different origin of the gas emission affect the mining exploit's gas emission quantity directly. In recent years, with the output of coal mining on the size and has expanded, coal mine safety production has become a major issue facing。Forecast ing the gas content depends on an establishment of a non liner funct ional relation of many factors; the accuracy of the forecasting model for the gas content is determined by the peculiarities of the in teract ion and coupling betw een all the af fect ing factors. This paper builds evaluation model of gas emission by means of deeply studying data mining technology and algorithm, deeply studies Apriori algorithm of association rules data mining and puts forward improving. The improved Apriori algorithm is used to mine the components data of gas emission in order to find valuable message, which can provide valuable references for forecasting gas content and Protecting Coal Mine Safety. Finally by simulation verification, On the basis of the data in laboratory, the training and test ing samples of improved Apriori model are founded, including 38 ty pical specimens. The verifying utcome has been compared w ith the output of back assay model, normal BP NN, and auto adapting NN. The result shows that the improved Apriori model is reliable and precise, w hich founds the basis for promot ing the integ rat ion of soft calculat ion and gas g eology .this model plays an indelible role in evaluation of gas emission.