A Novel Classification Approach through Integration of Rough Sets and Back-Propagation Neural Network

Table 1

The running status of shearer and its corresponding parameters.

Samples	𝐶1 (A)	𝐶2 (°C)	𝐶3 (A)	𝐶4 (°C)	𝐶5 (m/min)	𝐶6 (°)	𝐶7 (°)	𝐶8 (Hz)	Running status
1	45.12	78.74	65.46	88.16	3.51	2.52	45.12	628.85	0.78
2	48.19	75.22	70.78	84.28	3.42	3.62	53.22	683.46	0.79
3	50.25	80.19	85.14	91.25	2.88	5.36	40.22	705.76	0.82
4	45.26	82.43	62.45	84.15	3.12	2.85	49.36	642.14	0.76
5	64.28	77.16	90.45	91.41	2.56	2.26	58.55	823.29	1.22
6	46.22	85.24	68.55	80.46	3.26	2.86	58.46	711.24	0.83
7	72.56	85.12	102.42	102.36	2.76	10.26	38.41	881.25	1.17
8	62.33	74.24	92.46	84.46	3.56	8.26	60.27	821.46	1.12
9	44.23	89.19	63.15	85.78	3.82	3.22	46.25	578.26	0.75
10	89.23	81.24	120.36	86.14	2.01	1.05	50.36	1035.48	1.63
⋮	⋮	⋮	⋮	⋮	⋮	⋮	⋮	⋮	⋮
198	49.22	75.24	71.22	80.25	3.46	4.26	45.26	542.16	0.72
199	68.65	87.16	118.64	90.46	4.66	4.36	49.35	845.29	1.36
200	50.22	78.15	90.46	95.44	3.22	7.22	44.21	682.64	1.11