Aimed at that existing reasoning methods based on fuzzy Petri nets (FPN) and intuitionistic fuzzy Petri nets (IFPN) have the defects of complicated process and low efficiency in solving the problems only related to part of the knowledge base and they cannot analyze the causes of the problems

a hybrid reasoning method based on IFPN was presented.The method combined the forward reasoning and backward reasoning

firstly

the problems which needed to be solved were converted to goal places; secondly

in order to obtain potential causes of the problems and to simplify the reasoning model

associate places and transitions of goal places were searched by backward reasoning and a submodel was constructed; lastly

the problems of complicated process and low efficiency in using the original model to reason were solved by taking the submodel as the reasoning model and using forward reasoning to compute token values of goal places.Moreover

the real causes of the problems were found out by introducing threshold and the definition of route and active route into the model to remove the invalid associate places.The examples shows that the hybrid reasoning method is feasible and effective

and that compared with the existing methods shows that it overcomes the defects of the existing methods.