Research Article
Artificial Neural Networks Investigation of Indentation Force Effects on Nano- and Microhardness of Dual Phase Steels
Table 1
Range of 21 training parameters for nanohardness.
| | | Training parameters | Min | Max | Avr. | Std. Dev. |
| |
Input | F grain size (µm) | 0.7 | 3.9 | 1.87 | 1.48 | | M grain size (µm) | 0.82 | 1.4 | 1.03 | 0.27 | | MVF (%) | 22 | 34 | 27.33 | 5.11 | | Force (mN) | 0.25 | 12 | 3.96 | 4.23 |
| |
Target | F nanohardness (Gpa) | 2.31 | 4.2 | 2.95 | 0.49 | | F nanohardness tolerance (Gpa) | 0.05 | 0.72 | 0.29 | 0.19 | | M nanohardness (GPa) | 4.56 | 7.62 | 5.86 | 0.93 | | M nanohardness tolerance (GPa) | 0.25 | 5.75 | 1.58 | 1.4 |
|
|
