A Neural Network Diagnosis Model without Disorder Independence Assumption

摘要: Generally, the disorders in a neural network diagnosis model are assumed independent each other. In this paper, we propose for diagnostic problem solving where disorder independence assumption is no longer necessary. Firstly, characterize tasks and causal which used to represent problem, then describe model, finally, some experiment results will be given.