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

Table 4

K-HAT of each index varying with populations.

Population	Index
	K-HAT
	DBI	FCMI	PASI	DBFCMI	Average
30	0.36	0.34	0.24	0.48	0.34
60	0.35	0.24	0.07	0.33	0.25
75	0.37	0.31	0.29	0.39	0.34
90	0.32	0.21	0.16	0.36	0.26
Standard deviation	0.02	0.06	0.10	0.04	—

∗String length: 8, selection way: roulette wheel selection, crossover rate: 0.8, crossover way: two-point crossover, and mutation rate: 0.003.