Fuzzy reasoning and neural networks for decision making problems in uncertain environment

In the present paper, neural networks (NN) have been used to optimize the design of a generic expert system based on fuzzy logics. After building this fuzzy expert system, we isolate a set of parameters which are important for the system efficiency, and we show how these parameters can be optimized "automatically" using neural networks. This optimization brings an improvement over the manual tuning of the parameters in the specific case of a fuzzy expert system developed for the automatic target recognition of armoured vehicles starting from short-range infra-red images.<>