Research Article
The Bidirectional Optimization of Carbon Fiber Production by Neural Network with a GA-IPSO Hybrid Algorithm
Table 3
Errors of the proposed method, basic PSO-RNN, and conventional RNN (1: strength, 2: structure parameter).
| Algorithms | MAE | MRE (%) | RMSE | TIC | Time (s) |
| Conventional RNN | | | | | | 1 | 1.1950 | 28.63 | 1.4843 | 0.1675 | | 2 | 3.6827 | 27.96 | 4.5364 | 0.1452 | 0.9575 | Total | 2.4389 | 28.30 | 3.3750 | 0.1470 | |
| Basic PSO-RNN | | | | | | 1 | 0.4818 | 10.65 | 0.5841 | 0.0690 | | 2 | 2.0262 | 14.61 | 2.2637 | 0.0766 | 0.7428 | Total | 1.2540 | 12.63 | 1.6531 | 0.0761 | |
| Proposed method | | | | | | 1 | 0.4258 | 9.39 | 0.5157 | 0.0609 | | 2 | 1.9833 | 14.01 | 2.1177 | 0.0727 | 0.2985 | Total | 1.2045 | 11.70 | 1.5412 | 0.0718 | |
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