An Efficient Fitness Function in Genetic Algorithm Classifier for Landuse Recognition on Satellite Images

Table 7

Overall accuracy value of each model varying with crossover ways.

Crossover way	Index
	Overall accuracy (%)
	DBI	FCMI	PASI	DBFCMI	Average
P1	74.3	71.6	72.9	74.6	73.3
P2	71.6	73.2	64.9	75.5	71.3
P3	70.8	72.5	71.5	72.5	71.8
P4	68.8	74.5	68.9	74.7	71.7
P5	70.5	70.2	70.9	75.0	71.6
P6	68.7	64.2	56.0	75.0	73.3
Standard deviation	1.2	3.0	1.4	0.2	—

∗String length: 8, population: 30, selection way: roulette wheel selection, crossover rate: 0.8, and mutation rate: 0.003.