Bayesian elevator fault classifications network based on Stigmergy Strategy

To solve the complicated problem elevator fault classifications, a Bayesian confidence network structural learning algorithm based on Stigmergy is put forward. It was put into tests in the Bayesian network to diagnose elevator faults. With three fault datasets of the elevator of the same model, a Stigmergy Strategy based Bayesian Elevator Fault Classification Network, SSBCN for short, is constructed. In the 20 times of 10-crossing-over tests, the average classification accuracy of SSBCN experiments validates the effectiveness of the approach.