Research Article
Analysis System of MICE Tourism Economic Development Strategy Based on Machine Learning Algorithm
Table 8
Benchmark metrics for FFNN and other models.
| ā | Method | R 2 | RMSE | MAE | RRMSE | MRE | MAPE | Rank |
| Training | NMA | 0.73 | 0.065 | 0.053 | 0.088 | 0.027 | 2.574 | 6 | FFNN-ChOA | 0.98 | 0.017 | 0.015 | 0.012 | 0.036 | 0.640 | 42 | FFNN-IWT | 0.95 | 0.032 | 0.021 | 0.023 | 0.012 | 1.175 | 36 | MR | 0.87 | 0.040 | 0.033 | 0.053 | 0.018 | 1.653 | 24 | FFNN-NLBBO | 0.90 | 0.061 | 0.038 | 0.061 | 0.021 | 1.841 | 18 | FFNN-DA | 0.91 | 0.073 | 0.053 | 0.065 | 0.025 | 2.107 | 12 |
| Testing | NMA | 0.58 | 0.068 | 0.042 | 0.041 | 0.025 | 2.382 | 6 | FFNN-ChOA | 0.97 | 0.018 | 0.012 | 0.013 | 0.007 | 0.577 | 42 | FFNN-IWT | 0.94 | 0.027 | 0.018 | 0.016 | 0.013 | 0.984 | 36 | MR | 0.88 | 0.039 | 0.027 | 0.021 | 0.016 | 1.459 | 24 | FFNN-NLBBO | 0.82 | 0.043 | 0.030 | 0.027 | 0.018 | 1.666 | 18 | FFNN-DA | 0.76 | 0.044 | 0.034 | 0.029 | 0.020 | 1.860 | 12 |
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