These algorithms can
regulate the rates of crossover and mutation operators
during their search process. Kalaichelvi et al [14] applied
this combination in a metal arc welding process where the
non-linear welding parameter selection was controlled via
fuzzy-genetic technique. Another implementation of fuzzy
logic to welding operation was reported by Hang et.al [15]
where the objective was to enhance the control performance
of the two-inputs-two outputs fuzzy welding system. Also,
Cntra et al [16] applied genetic fuzzy implementation to
enhance rule selection from an existing data. The results
were compared according to interpretability and accuracy of
the system. This paper will review the concept of Genetic
Fuzzimetric technique, the concept of Fuzzimetric Arcs and
then produce definitions and terminologies used in GFT as
well as the mechanism of its operation. Section IV will
identify and discuss the advantages of the technique as
compared to traditional fuzzy system and sections V and VI
describes an application of student’s GPA prediction based
on the concepts detailed in sections II and III.