Fig. 8: Model fine-tuning results for the optimal dataset size. | Nature Communications

Fig. 8: Model fine-tuning results for the optimal dataset size.

From: Scale-up of complex molecular reaction system by hybrid mechanistic modeling and deep transfer learning

Fig. 8

a Parity plot for product yield of naphtha 2 FCC in the training set. b Parity plot for product yield of naphtha 2 FCC in the validation set. c Parity plot for product yield of naphtha 2 FCC in the testing set. d Predicted product yield for naphtha 3 FCC under the following process conditions: Feedstock temperature = 200 °C, Catalyst temperature = 623 °C, Catalyst-to-oil ratio (CTO) = 5.5, and reaction time = 3.6 s. e Parity plot for gasoline composition of naphtha 2 FCC in the training set. f Parity plot for gasoline composition of naphtha 2 FCC in the validation set. g Parity plot for gasoline composition of naphtha 2 FCC in the testing set. h Predicted gasoline composition for naphtha 3 FCC under the same process conditions as d. The mean absolute error (MAE) for training, validation, and testing sets is reported in the figure. Source data are provided as a Source data file.

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