Research on multi-source data fusion model of safety monitoring for oil depot

The multi-source data fusion model has been established via organically combining Fuzzy neural network and Particle swarm optimization, to ensure safety monitoring of oil depot in complex environments. The method to pretreat the data collected has been given to eliminate the interference. Multi-source data fusion algorithm based on fuzzy neural network, which embeds the fuzzy reasoning rule into fuzzy neural network, has been designed. Particle Swarm Optimization algorithm is used to train fuzzy neural network weights, truncate redundant links and optimize data fusion fuzzy rule base. According to sufficient experiments´ simulation, it shows that the multi-source data fusion model could efficiently realize the assessment of oil depot´s security, reduce the probability of false alarms and missing checking. The research the multi-source data fusion model has a superior value in the practice.