Quadrilateral Interval Type-2 Fuzzy Regression Analysis for Data Outlier Detection

Table 1

A set of interval type-2 trapezoidal fuzzy numbers.

1	((1, 38.09, 36.43, 5), (1, 43.09, 41.43, 5))
2	((1, 62.10, 26.50, 6), (1, 67.10, 31.50, 6))
3	((1, 63.76, 44.71, 7), (1, 68.76, 49.71, 7))
4	((1, 74.52, 38.09, 8), (1, 79.52, 43.09, 8))
5	((1, 75.38, 41.40, 7), (1, 80.38, 46.40, 7))
6	((2, 52.99, 26.49, 4), (2, 57.99, 31.49, 4))
7	((2, 62.93, 26.49, 5), (2, 68.93, 31.49, 5))
8	((2, 72.04, 33.12, 6), (2, 77.04, 38.12, 6))
9	((2, 76.12, 43.06, 7), (2, 81.12, 47.06, 7))
10	((2, 90.26, 42.64, 7), (2, 95.26, 47.64, 7))
11	((3, 85.70, 31.33, 6), (3, 90.70, 36.33, 6))
12	((3, 95.27, 27.64, 6), (3, 100.27, 32.64, 6))
13	((3, 105.98, 27.64, 6), (3, 110.98, 32.64, 6))
14	((3, 79.25, 66.81, 6), (3, 84.25, 71.81, 6))
15	((3, 120.5, 32.25, 6), (3, 125.5, 37.25, 6))