Macroscopic Rock Texture Image Classification Using a Hierarchical Neuro-Fuzzy Class Method

Table 10

Fuzzy rules.

Rules		Accuracy	Coverage
Rule $1$	If X8 is low and X12 is low and X6 is low then Class = 1	0.6813	0.1105
Rule $2$	If X8 is low and X12 is low and X6 is high and X3 is low then Class = 1	0.548	0.06137
Rule $3$	If X8 is low and X12 is low and X6 is high and X3 is high then Class = 1	0.5152	0.05707
Rule $4$	If X8 is low and X12 is high and X10 is low and X2 is low then Class = 1	0.5013	0.03149
Rule $5$	If X8 is low and X12 is high and X10 is low and X2 is high then Class = 2	0.5159	0.02537
Rule $6$	If X8 is low and X12 is high and X10 is high and X4 is low then Class = 1	0.5801	0.01211
Rule $7$	If X8 is low and X12 is high and X10 is high and X4 is high then Class = 2	0.5648	0.01475
Rule $8$	If X8 is high and X7 is low then Class = 1	0.5601	0.09951
Rule $9$	If X8 is high and X7 is high and X11 is low and X8 is low then Class = 1	0.5388	0.02845
Rule $10$	If X8 is high and X7 is high and X11 is low and X8 is high then Class = 2	0.6614	0.03755
Rule $11$	If X8 is high and X7 is high and X11 is low and X12 is low then Class = 2	0.5931	0.01464
Rule $12$	If X8 is high and X7 is high and X11 is low and X12 is high then Class = 2	0.5676	0.01653