Study of hybrid learning algorithms for realization of self-constructing fuzzy neural networks - Liu, Fan. (2012)
Fuzzy neural networks (FNNs) have learning ability and adaptive capability. Usually, the typical approaches of designing an FNN are to build standard neural networks (NNs) which are designed to approximate a fuzzy algorithm or a process of the fuzzy inference system (FIS) through the structure of NNs. The parameters of FNNs can be updated by using learning algorithms of NNs. Therefore, the human-like thinking and reasoning of fuzzy logic systems and the learning and computational ability of NNs can be combined in FNNs.