Optimal Maintenance Decision Method for a Sensor Network Based on Belief Rule Base considering Attribute Correlation

Table 6

Optimized health assessment model for WSN.

No.	Rule weight	Characteristic		Output distribution of belief rule
		CR	FR	{L, SL, M, SH, and H}
1	0.2237	L	L	(0.1941 0.3806 0.0839 0.0605 0.2809)
2	0.0340	L	SL	(0.0366 0.2194 0.4384 0.0619 0.2438)
3	0.4825	L	M	(0.2308 0.1866 0.2243 0.2737 0.0848)
4	0.9214	L	SH	(0.2901 0.2480 0.0365 0.0285 0.3968)
5	0.1094	L	H	(0.1499 0.4173 0.0806 0.2005 0.1517)
6	0.0213	M	L	(0.0278 0.4044 0.3744 0.0823 0.1112)
7	0.8192	M	SL	(0.9246 0.0103 0.0564 0.0000 0.0226)
8	0.0745	M	M	(0.3313 0.2423 0.2751 0.0995 0.0519)
9	0.1110	M	SH	(0.3338 0.1885 0.2150 0.0755 0.1872)
10	0.3228	M	H	(0.4458 0.1847 0.1215 0.1488 0.0992)
11	0.4260	SH	L	(0.1800 0.1473 0.0343 0.4604 0.1780)
12	0.2566	SH	SL	(0.5815 0.1738 0.1383 0.0733 0.0332)
13	0.8864	SH	M	(0.8368 0.0646 0.0500 0.0424 0.0063)
14	0.3489	SH	SH	(0.4968 0.0901 0.1494 0.1831 0.0806)
15	0.4101	SH	H	(0.1739 0.2406 0.3724 0.0390 0.1741)
16	0.1775	H	L	(0.0580 0.3663 0.2701 0.2254 0.0802)
17	0.9738	H	SL	(0.1383 0.5759 0.1463 0.0329 0.1066)
18	0.0559	H	M	(0.1947 0.0924 0.1375 0.0333 0.5422)
19	0.0907	H	SH	(0.2482 0.1992 0.2872 0.1637 0.1017)
20	0.8838	H	H	(0.1363 0.4430 0.1582 0.1333 0.1292)