Research Article
Soft Sensing Modeling of the SMB Chromatographic Separation Process Based on the Adaptive Neural Fuzzy Inference System
Table 5
Comparison of predictive performance indicators of the ANFIS soft sensor model based on the FCM clustering method.
| Performance | RMSE | SSE | MAPE | MPE |
| Purity of the E port | Gradient | 0.0643 | 0.8281 | 0.0258 | 0.8410 | Kalman | 0.0485 | 0.4699 | 0.0258 | 0.5163 | Kaczmarz | 0.0517 | 0.5344 | 0.0196 | 0.6431 | PseudoInv | 0.0440 | 0.3874 | 0.0253 | 0.4297 |
| Purity of the R port | Gradient | 0.1245 | 3.0982 | 0.5547 | 0.4398 | Kalman | 0.087 | 1.5336 | 0.5557 | 0.4262 | Kaczmarz | 0.1131 | 2.5603 | 0.6397 | 0.5862 | PseudoInv | 0.0837 | 1.4009 | 0.5558 | 0.4129 |
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