A Novel Model Using Virtual State Variables and Bayesian Discriminant Analysis to Classify Surrounding Rock Stability

Table 1

The collected samples.

No.	RQD (%) x1	(MPa) x2	x3	Kfx4	(L/min.10 m) x5	Actual output
1	43.8	26.3	0.28	0.35	50	IV
2	37.5	22.5	0.25	0.3	75	IV
3	31.3	18.8	0.23	0.25	100	IV
4	26	36	0.22	0.35	5	IV
5	50	40.2	0.5	0.5	10	III
6	52	25	0.2	0.5	5	III
7	71	90	0.35	0.3	18	III
8	75	95	0.7	0.5	0	II
9	77.5	90	0.57	0.45	10	II
10	50	70	0.5	0.25	5	III
11	50.9	34	0.32	0.35	21	III
12	31.5	20	0.23	0.25	46	IV
13	50.6	26	0.26	0.35	20	III
14	75.5	90	0.45	0.52	8	II
15	85.5	94	0.65	0.55	0	II
16	80	95	0.5	0.45	0	II
17	35	70.5	0.35	0.3	10	III
18	50	90	0.5	0.25	5	III
19	85	93	0.6	0.5	0	II
20	78.5	92	0.55	0.5	6	II
21	30.2	70	0.4	0.2	10	III
22	85	92	0.7	0.5	10	II
23	51	35	0.32	0.35	15	III
24	87	95	0.5	0.45	0	II
25	82	96	0.75	0.35	0	II
26	52.5	30.5	0.38	0.15	25	IV
27	78	80	0.75	0.5	0	II
28	85	92	0.7	0.5	10	II
29	50	45	0.12	0.3	5	III
30	31.5	20	0.23	0.25	50	IV
31	76.5	90	0.55	0.5	10	II
32	85	95	0.65	0.5	0	II
33	50.9	34	0.32	0.35	20	III
34	75	90	0.55	0.5	7	II
35	75	90	0.55	0.5	10	II
36	50	45	0.15	0.35	5	III
37	75	70	0.72	0.53	12	II