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A TSK-type recurrent fuzzy network for dynamic systems processing by neural network and genetic algorithms
2002
IEEE transactions on fuzzy systems
In this paper, a TSK-type recurrent fuzzy network (TRFN) structure is proposed. The proposal calls for a design of TRFN by either neural network or genetic algorithms depending on the learning environment. Set forth first is a recurrent fuzzy network which develops from a series of recurrent fuzzy if-then rules with TSK-type consequent parts. The recurrent property comes from feeding the internal variables, derived from fuzzy firing strengths, back to both the network input and output layers.
doi:10.1109/91.995118
fatcat:7f2xefwopjc7vgqrihcrfpobxq