Prediction model of working face hypoxia based on improved generalized regression neural network

Inordertosolvetheproblemofworkingfacehypoxiaincoalminemoreeffectivelyandreasonably,animprovedgeneralneuralnetwork(GRNN)modelforpredictionofoxygenconcentrationin coalminewasconstructed,bytakingthemonitoringdataofaworkingfaceinShendongassamplesand consideringtheinteractionrelationshipbetweenphysicalparameters,basedonprincipalcomponentanalysis.Comparingthepredictedoxygenconcentrationresultswiththemeasureddata,itprovesthatthe improvedGRNN model has good fitting accuracy and generalization ability.By using the improved GRNNmodel,theoriginalGRNNmodelandBPneuralnetworkmodelrespectivelyinthecomparative analysisofhypoxiaproblems,itfoundthattheimprovedGRNNmodelhasbettereffectsandismore suitableforthepredictionofhypoxiaproblemsincoalmineface.Theinfluenceofinletairpressure, outletairpressureandinletairtemperatureontheoxygenconcentrationwereanalyzedbytheimproved GRNNmodel.ThisimprovedGRNNmodelcangiveareferencetohypoxiapredictionandhypoxiacontroltechnologyoftheworkingface.