Multi-sensor information fusion based on integration of GA-BP network and D-S evidence theory
GA-BP网络与D-S证据相结合的多传感器信息融合

As back propagation network and dempster-shafer evidence theory have individual defects in processing uncertain information, a method of multi-sensor information fusion is proposed based on the combination of genetic algorithms optimal BP neural network and D-S evidence theory. The basic probability assignment of D-S evidence theory can be obtained using GA-BP network. moreover, the results of GA-BP network output can be fused by D-S evidence theory. The method is applied to fault diagnosis of high-voltage electric equipment. Simulation shows that the new method can solve the locally optimal problem in single BP neural network training, and get a better recognition result.