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

Table 4

Comparison between initial generation and optimization.

q	The proportion of the number of grids (%)
	Initial grid			After optimization
	Case 1	Case 2	Case 3	Case 1	Case 2	Case 3
0.9 ≤ q ≤ 1	85.79	75.36	78.85	92.03	95.87	93.69
0.8 ≤ q ＜ 0.9	8.64	16.04	13.37	6.70	3.54	5.27
0.7 ≤ q ＜ 0.8	2.85	5.35	3.78	0.78	0.42	0.68
0.6 ≤ q ＜ 0.7	1.53	1.71	1.64	0.27	0.12	0.19
Q ＜ 0.6	1.19	1.52	2.36	0.24	0.05	0.17