An Automatic Isotropic Triangular Grid Generation Technique Based on an Artificial Neural Network and an Advancing Front Method

Table 3

Normalized training dataset of a typical edge (or front).

Input								Output
										Type
−0.1579	−1.7899	0	0	1	0	1.7876	−0.9422	0.3962	1.7117	1
−0.1579	−1.7899	0	0	1	0	2.8634	0.8872	0.3962	1.7117	1
−0.1579	−1.7899	0	0	1	0	0.3962	1.7117	0.3962	1.7117	3
−1.2383	0.0782	0	0	1	0	−0.1579	−1.7899	0.3962	1.7117	1
−1.2383	0.0782	0	0	1	0	1.7876	−0.9422	0.3962	1.7117	1
−1.2383	0.0782	0	0	1	0	2.8634	0.8872	0.3962	1.7117	1
−1.2383	0.0782	0	0	1	0	0.3962	1.7117	0.3962	1.7117	3
0.3962	1.7117	0	0	1	0	−0.1579	−1.7899	0.3962	1.7117	2
0.3962	1.7117	0	0	1	0	1.7876	−0.9422	0.3962	1.7117	2
0.3962	1.7117	0	0	1	0	2.8634	0.8872	0.3962	1.7117	2