Table 1.
Illustrations of design elements and features of a men’s suit
| Attribute (Design element) | Level (Design feature) |
|---|---|
| FABRIC(A) |  |
| COLOR(B) |  |
| SILHOUETTE (C) |  |
| COLLAR OPENING (D) |  |
| BOTTOM HEM (E) |  |
| COLLAR TYPE (F) |  |
| WAIST POCKET (G) |  |
Fig. 1.
Illustration of suit samples
Fig. 2.
BP neural network structure
Fig. 3.
Result parameters of BP neural network
Fig. 4.
Error curve of BP neural network
Table 2.
Actual value and predicted value of consumer preference
| Actual value of consumer preference | Normalization of actual value | Predicted value of consumer preference | Normalization of predicted value |
|---|---|---|---|
| 0.49 | 0.50 | 0.15 | 0.00 |
| 0.57 | 1.00 | 0.78 | 1.00 |
| 0.56 | 0.94 | 0.19 | 0.07 |
| 0.43 | 0.13 | 0.74 | 0.93 |
| 0.44 | 0.19 | 0.34 | 0.30 |
| 0.41 | 0.00 | 0.23 | 0.14 |
Fig. 5.
Design flow of integrated algorithm
Table 3.
Optimization scheme of a men’s suit
| Design element | Design feature | Graphical Presentation |
|---|---|---|
| Fabric (A) | Solid color (A1) |  |
| Color (B) | Black (B1) |  |
| Silhouette (C) | V (C1) |  |
| Collar opening (D) | Single row 3 button (D3) |  |
| Bottom hem (E) | Big rounded corner (E3) |  |
| Collar type (F) | Shawl collar (F3) |  |
| Waist pocket (G) | Double-besom pocket (G1) |  |
Fig. 6.
Optimization scheme of a men’s suit