Model of Coal Mine Gas Safety Early Warning System Based on SSA-SVM
At present,coal mine gas early warning mainly focuses on gas concentration monitoring.Considering the impact of other environmental factors on coal mine gas safety,an improved Sparrow Search Algorithm(BCSSA)is proposed to optimize SVM parameters and integrate multiple environmental parameters to classify gas safety levels for warning.Firstly,BCSSA introduced Bernoulli mapping and Cauchy mutation were used to solve the problem of uneven initialization and susceptibility to local optima in the sparrow search algorithm.Secondly,the BCSSA-SVM safety warning model was established,and the coal mine gas safety level was divided into four levels according to the ″coal mine safety Regulations″.Finally,the algorithm performance and model were simulated respectively.The simulation results show that the performance of BCSSA algorithm is significantly improved,and the accuracy of BCSSA-SVM model is significantly improved compared with other models.
GasSparrow search algorithmSupport vector machinesEarly warning model
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