## 1 Introduction
These models, applied here for the first time in this context, use temperature, pressure, and salinity as inputs. Results confirm salinity as the second most influential factor after temperature due to its effect on solvent viscosity, density, and molecular mobility. The workflow is summarized in Figure 2, and the findings provide a robust, data-driven approach to support CO\({}_{2}\) CCS and EOR design. \begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Source** & **Model** &
\begin{tabular}{c} **Data Points** \\ **(Train/Test)** \\ \end{tabular} & **Parameters (Ranges)** & **Train Metrics** & **Test Metrics** \\ \hline [PERSON] et al. \\ (2019) [32] & \multirow{4}{*}{MKSVM-GA} & \multirow{4}{*}{92 (72/20)} & T: 273–473.15 K & R\({}^{2}\): 0.9975 & R\({}^{2}\): 0.9910 \\  & & P: 0.1–49.3 MPa & MAE: 0.1112 \(\times\) 10\({}^{-9}\) m\({}^{2}\)/s & MAE: 0.2028 \(\times\) 10\({}^{-9}\) m\({}^{2}\)/s \\  & & & \(\mu\): 0.139–1.950 mPa-s & RMSE: 0.1527 \(\times\) 10\({}^{-9}\) m\({}^{2}\)/s & RMSE: 0.3028 \(\times\) 10\({}^{-9}\) m\({}^{2}\)/s \\  & & & & MAE: 7.717\% & MAE: 10.55\% \\  & & & & R\({}^{2}\): 0.9993 & R\({}^{2}\): 0.9978 \\  & PSO-ANFIS & & & MARE: 2.0945\% & MARE: 2.7188\% \\ Bemani et al. & \multirow{4}{*}{64 (N/A)} & T: 273–473.15 K & RMSE: 0.0869 & RMSE: 0.113 \\  & & & P: 0.1–49.3 MPa & R\({}^{2}\): 0.9957 & R\({}^{2}\): 0.9932 \\  & & & \(\mu\): 0.139–1.950 Pa-s & MARE: 4.2591\% & MARE: 4.9245\% \\  & & & & RMSE: 0.2156 & RMSE: 0.1976 \\  & & & & R\({}^{2}\): 0.9924 & R\({}^{2}\): 0.9854 \\  & ACO-ANFIS & & & MARE: 5.9726\% & MARE: 6.6933\% \\  & & & & RMSE: 0.2877 & RMSE: 0.3161 \\  & & & & R\({}^{2}\): 0.9862 & R\({}^{2}\): 0.9738 \\  & BP-ANFIS & & & MARE: 12.2787\% & MARE: 12.787\% \\  & & & & RMSE: 0.3905 & RMSE: 0.398 \\  & & & & R\({}^{2}\): 0.9708 & R\({}^{2}\): 0.9514 \\  & DE-ANFIS & & & MARE: 14.545\% & MARE: 15.965\% \\  & & & & RMSE: 0.633 & RMSE: 0.633 \\  & & & & R\({}^{2}\): 0.9980 & R\({}^{2}\): 0.9978 \\ Amar et al. & \multirow{4}{*}{GEP} & T: 273,473.15 K & AARD: 3.8584\% & AARD: 6.0035\% \\ (2020) [34] & & P: 0.1–49.3 MPa & RMSE: 0.1427 \(\times\) 10\({}^{-9}\) m\({}^{2}\)/s & RMSE: 0.1245 \(\times\) 10\({}^{-9}\) m\({}^{2}\)/s \\  & & & \(\mu\): 0.139–1.950 mPa-s & R\({}^{2}\): 0.9943 & R\({}^{2}\): 0.9874 \\  & GMDH & & & ARARD: 8.6269\% & AARD: 5.6292\% \\  & & & & RMSE: 0.22479 \(\times\) 10\({}^{-9}\) m\({}^{2}\)/s & RMSE: 0.2271 \(\times\) 10\({}^{-9}\) m\({}^{2}\)/s \\  & & & & R\({}^{2}\): 0.9979 & R\({}^{2}\): 0.9965 \\  & MLP & & P: 0.10–100 MPa & RMSE: 2.7521 & RMSE: 3.4812 \\ [PERSON] et al. & \multirow{4}{*}{191 (80/20)} & T: 210–673 K & MAE: 1.6421 & MAE: 2.3647 \\  & & & Brine Density: 98.38–1400 kg/m\({}^{3}\) & R\({}^{2}\): 0.9968 & R\({}^{2}\): 0.9949 \\  & CFNN & & DC: 0.0007–285 \(\times\) 10\({}^{-9}\) m\({}^{2}\)/s & RMSE: 3.6024 & RMSE: 5.2113 \\  & & & & MAE: 2.4597 & MAE: 3.9210 \\  & & & & R\({}^{2}\): 0.9974 & R\({}^{2}\): 0.9958 \\  & RNN & & & RMSE: 2.9021 & RMSE: 4.8735 \\  & & & & MAE: 1.8890 & MAE: 3.2241 \\  & & & & R\({}^{2}\): 0.9938 & R\({}^{2}\): 0.9918 \\  & GEP & & & RMSE: 5.1432 & RMSE: 5.4981 \\  & & & & MAE: 4.0023 & MAE: 4.3184 \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Comparison of models and evaluation metrics for predicting CO\({}_{2}\) diffusion performance.