Context Adaptation of Fuzzy Inference System-Based Construction Labor Productivity Models

Table 2

Context adapted models’ sensitivity analysis: linearly and nonlinearly adapted institutional model.

Case	Fuzzy operators and defuzzification methods
	Input aggregation	Implication method	Rule aggregation	Defuzzification method	Linearly adapted model accuracy ()	Nonlinearly adapted model accuracy
1	MIN	MIN	MAX	CENTROID	1.840	2.742
2	MIN	MIN	MAX	BISECTOR	1.840	2.742
3	MIN	MIN	MAX	MOM	1.955	2.766
4	MIN	MIN	MAX	LOM	2.030	2.762
5	MIN	MIN	MAX	SOM	1.955	2.766
6	MIN	MIN	SUM	CENTROID	1.840	2.742
7	MIN	MIN	SUM	BISECTOR	1.840	2.742
8	MIN	MIN	SUM	MOM	1.955	2.766
9	MIN	MIN	SUM	LOM	2.030	2.762
10	MIN	MIN	SUM	SOM	1.955	2.766
11	MIN	MIN	PROBOR	CENTROID	1.840	2.742
12	MIN	MIN	PROBOR	BISECTOR	1.840	2.742
13	MIN	MIN	PROBOR	MOM	1.955	2.766
14	MIN	MIN	PROBOR	LOM	2.030	2.762
15	MIN	MIN	PROBOR	SOM	1.955	2.766
16	PROD	PROD	MAX	CENTROID	1.832	2.738
17	PROD	PROD	MAX	BISECTOR	1.840	2.740
18	PROD	PROD	MAX	MOM	1.955	2.765
19	PROD	PROD	MAX	LOM	2.030	2.762
20	PROD	PROD	MAX	SOM	1.955	2.765
21	PROD	PROD	SUM	CENTROID	1.832	2.738
22	PROD	PROD	SUM	BISECTOR	1.840	2.740
23	PROD	PROD	SUM	MOM	1.840	2.740
24	PROD	PROD	SUM	LOM	2.030	2.762
25	PROD	PROD	SUM	SOM	1.955	2.765
26	PROD	PROD	PROBOR	CENTROID	1.832	2.738
27	PROD	PROD	PROBOR	BISECTOR	1.840	2.742
28	PROD	PROD	PROBOR	MOM	1.955	2.766
29	PROD	PROD	PROBOR	LOM	2.030	2.762
30	PROD	PROD	PROBOR	SOM	1.955	2.766