Research on the safety risk early warning method of the apron based on RS-IPSO-SVM

For better resolving the safety risk early warning of the apron effectively, the attribute reduction algorithm based on Rough Set is used to simplify the set as the warning index set of the apron is too large. The improved Particle Swarm Optimization (PSO) algorithm is used to optimize the parameters of Support Vector Machine. Combined with the Rough Set and SVM which is optimized by the improved Particle Swarm Optimization algorithm, a safety risk early warning method based on RS-IPSO-SVM is designed. Finally, with the data of the apron, the experimental results show that the method has higher warning accuracy, and has practical value to the safety risk early warning of the apron.