## 3 Methodology
### Data Collection and Pre-Processing
\begin{table}
\begin{tabular}{c c c c} \hline \hline
**Measurement Device** & **Specific Information** & **Ranges** & **Accuracy** \\ \hline \multirow{2}{*}{Temperature sensor (\({}^{\circ}\)C)} & RTD (OMEGA) & \(-\)50-200 & \(\pm\)0.15\% \\  & HOBO U12 (ONSET) & \(-\)20–70 & \(\pm\)0.35\% \\ \multirow{2}{*}{Flow meter (m\({}^{3}\)/h)} & FMAG 5000 (SiEMENS) & 0–400 & \(\pm\)0.4\% \\ \multirow{2}{*}{Power meter} & CW240 (YOKOGAWA) & 0–3000 & \(\pm\)0.6\% \\ \hline \hline \end{tabular}
\end{table} 
Table 7: Accuracy of the measurement devices. \begin{table}
\begin{tabular}{c c} \hline \hline
**Category** & **Unit** & **Symbol** \\ \hline Outdoor air temperature & \({}^{\circ}\)C & \(T_{OA}\) \\ Source side inlet temperature & \({}^{\circ}\)C & \(T_{S,j}\) \\ Source side outlet temperature & \({}^{\circ}\)C & \(T_{S,\rho}\) \\ Load side inlet temperature & \({}^{\circ}\)C & \(T_{L,j}\) \\ Load side outlet temperature & \({}^{\circ}\)C & \(T_{L,\rho}\) \\ Heat pump power & kW & \(W_{HP}\) \\ COP & - & _COP_ \\ Pump power & kW & \(W_{P}\) \\ \hline \hline \end{tabular}
\end{table} 
Table 8: Operation data list. \begin{table}
\begin{tabular}{c c} \hline \hline
**Category** & **Uncertainty (\%)** \\ \hline Temperature & 0.2 \\ Flow rate & 0.26–0.32 \\ \hline \hline \end{tabular}
\end{table} 
Table 9: Measurement uncertainty. n: Number of data  
\(\mathbf{X_{i}}\): Input data  
\(\overline{\mathbf{X}}\): Average of input data  
\(\mathbf{Y_{i}}\): Output data  
\(\overline{\mathbf{X}}\): Average of output data  
The Pearson correlation coefficient is a number from 1 to \(-1\). As the value of the correlation coefficient approaches 0, the relationship between the input and output data is weaker. The coefficient of determination indicates the correlation between two variables to be measured; a coefficient closer to 1 indicates better performance. The inlet temperature, outlet temperature, load-side inlet temperature, outlet temperature, and outdoor temperature were used as the input. The monitored items with a high correlation coefficient between input data and output data of less than 0.2 and a coefficient of determination of less than 0.04 among the performance coefficient theoretical equation were selected as variables. Table 10 lists the analysis results of the determination coefficient and Pearson correlation coefficient for the input and output data for the selected input variable. The heat-source-side outlet temperature showed the highest correlation among the input variables, with a Pearson correlation coefficient of \(-0.76\) and a coefficient of determination of 0.58. The outdoor temperature had a Pearson correlation coefficient of 0.32 and a coefficient of determination of 0.10, indicating a relatively small relationship among the input variables. The data of the input variables, such as the inlet temperature on the heat source side, outlet temperature on the heat source side, load side inlet temperature, load side outlet temperature, and outdoor temperature, are the learning data by deleting the data in the non-operational state of the geothermal system and excluding abnormal data (null) values. (Training data), validation data (Testing data), and evaluation data (Validation data) to generate training data for predictive model development.