The GFT is based on a biological analogy to represent an
optimized system solution. In this technique, each rule-set
describing the fuzzy relation (input * output) is considered a
chromosome. The GFT then mutates the genes within these
chromosomes to achieve an optimized performance. The
main advantage of using GFT is its modular structure that
allows the system to be built in modules or chromosomes.
Each chromosome represents the rule-set between a specific
input Xi and a specific output Yj combined in a fuzzy
relation. The defuzzified output Yj is then multiplied by an
input importance weighting factor to achieve discrete output
Yj as a result of specific input Xi.