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Real/binary-like coded versus binary coded genetic algorithms to automatically generate fuzzy knowledge bases: a comparative study
2004
Engineering applications of artificial intelligence
Nowadays fuzzy logic is increasingly used in decision-aided systems since it offers several advantages over other traditional decision-making techniques. The fuzzy decision support systems can easily deal with incomplete and/or imprecise knowledge applied to either linear or nonlinear problems. This paper presents the implementation of a combination of a Real/Binary-Like coded Genetic Algorithm (RBLGA) and a Binary coded Genetic Algorithm (BGA) to automatically generate Fuzzy Knowledge Bases
doi:10.1016/j.engappai.2004.04.006
fatcat:4y3bamamenhjzdybwqto3u3uuu