Developing an IFC-Based Database for Construction Quality Evaluation

Table 3

BP neural network sample data.

Evaluation index no. (Ei)	Ei1	Ei2	Ei3	Ei4	Ei5	Ei6	Ei7	Ei8	Ei9	Ei10	Ei11	Ei12	Ei13	Ei14	Ei15	Ei16	Ei17
1	10	3.07	4.82	6.6	5.4	5.33	10	10	10	3.77	3.95	4.91	3.68	1	1	0.9	96.3
2	10	2.94	4.5	5.92	5.1	5.29	9	10	9	3.42	2.6	4.55	5.11	0.95	0.9	1	94.9
3	8.5	3.88	6.27	5.5	7.19	5.5	8.5	8	8.5	5.26	6.1	7.33	6.54	0.8	0.85	0.8	83
4	8.5	4.17	6.4	7.39	6.4	6.96	7	8.5	8	4.92	5.97	8.5	7.29	0.8	0.92	0.8	79.75
5	7	4.28	6.97	7.21	6.99	8.1	8	8	7	7.2	8.9	8.94	7.11	0.84	0.9	0.95	76.7
6	7.5	4.05	7.83	5.5	7.93	5.22	7	9	8.5	6.91	9.22	9.59	7.36	0.82	0.88	0.8	77.75
7	8	4.39	7.1	8.87	8.2	9.24	8.5	8	7	7.09	8.36	8.91	6.8	1	0.91	0.95	79.05
8	10	2.97	5.15	4.2	4.96	5.52	9	9	9	3.42	4.22	3.88	4.07	0.8	0.95	0.9	93.15
9	9	4.05	7	7.27	6.9	6.08	8	9	7	6.18	7.01	9.12	7.03	0.9	0.84	0.8	80.1
10	10	3.31	4.91	6.11	4.92	8.34	9	10	10	3.81	4	6.21	5.7	0.85	0.9	0.86	92.3
11	8.5	4.02	5	6.6	4.37	5.13	8.5	9	8.5	5.3	6.12	7.52	6.21	0.8	0.8	1	85.15
12	7	4.67	7.44	5.59	7	7.19	7	8	7	7.1	8.76	9.71	7.6	0.85	0.9	0.9	73.9
13	9	3.04	5.11	4.9	5.34	4.98	8.5	10	8.5	4.05	2.92	5.8	4.5	0.82	0.85	0.8	89.95
14	8.5	3.95	6.44	3.92	7.02	5.71	9	10	10	4.3	6.97	7.17	6.22	0.9	0.9	0.8	87.65
15	9	4.01	6.67	5.5	5.41	7.32	7.5	8.5	8.5	3.59	6.16	6.93	5.63	0.95	0.94	0.85	86.15
16	10	3.4	5.66	4.74	6	7.99	10	10	9	4.89	5.05	5.3	4	0.85	0.8	0.9	91.5
17	9	3.25	7	8.81	5.03	6.77	9	10	8.5	7.29	8.17	8.69	7.6	0.8	0.95	0.85	85.35
18	10	3.5	7.83	5	7.95	5.2	10	9	9	4	5.26	5.61	3.9	0.9	0.9	1	91.85
19	10	3.44	5.16	6.11	6.81	4.73	10	10	10	6.5	9.73	9	7.4	0.8	0.82	0.8	88.3
20	8.5	4.1	5.55	5.45	5.17	6.59	9	10	9	6.11	6	7.95	7.03	0.85	0.8	0.95	85.35
21	9	4.34	6.77	6.65	7	8.09	10	10	10	6.08	9.29	9.19	7.83	0.9	1	0.9	86.6
22	10	3.91	6.71	8.19	7.22	4.54	10	10	9	4.07	3.87	4.96	6.6	0.85	0.8	0.9	89.8
23	9	3.19	6.9	4.15	5.02	5.54	10	10	9	5.01	8.8	8.36	7.73	0.85	0.8	0.8	87
24	8.5	3.02	3.95	5.9	5.06	7	9	10	9	5.5	8.14	7.9	7.11	0.93	0.85	0.9	86.15