## 4 Validation through BIM Application in Planning Stage
### Model Conformity Evaluation  
Table 6 presents the results of applying the data from the 10 cases selected for testing (as described in Section 4.2) to the cost prediction model developed in this study. In the model validation process, the coefficient of determination and mean absolute percentage error (MAPE), derived by applying the corresponding 10 datasets, were used, and in order to measure the ratio of data with an error percentage of 10% or less, a custom evaluation index called \"precision\" was also used. By verifying the cost prediction model for the 10 datasets of the BIM setup using the evaluation indices, the coefficient of determination was found to be 0.95036, confirming that the cost prediction model effectively explains the data distribution. Furthermore, the MAPE was 0.08850, and precision was 0.7. Based on  
Figure 9: Test BIM setup for validation. Based on the numerical results in Table 6, the adequacy and practical applicability of the cost prediction model were evaluated based on the accuracy range presented by AACE [8], as summarized in Table 7. Considering the scope of this study, among the accuracy ranges obtained by division into five classes, the conformity of the cost prediction model was evaluated based on Class 5. Class 5 estimates are generally made based on extremely limited information, after which they are characterized as having a wide range of accuracies; the architectural planning stage (pre-design phase) corresponds to this case. The ACCE Class 5 phase is implemented when the project has progressed approximately 0-2%, a stage in which it is necessary to collect information regarding the project location and owner requirements and to calculate the construction cost rapidly. The estimates obtained in this stage mainly provide information for the economic evaluation of the project, such as market research, early feasibility evaluation, alternative plan evaluation, and budgeting. Because the objective of this study was conceptual cost estimation in the architectural planning stage, the standards of Class 5 were adopted. Based on the test results in Table 6 obtained using the cost prediction model developed in this study, the interpretation of the results by applying the AACE standard can be summarized as shown in Table 8. By applying the data from 10 cases to the cost prediction model, the error rate for each dataset could be obtained, and these values were substituted into the accuracy range and design stage of the AACE standard to evaluate the conformity of the cost prediction model. The expected accuracy range of Class 5, assuming that the project is in the planning stage, can be as low as\(-20\%\) to \(-50\%\) or as high as \(30\%\) to \(100\%\) depending on the technical complexity of the project and the risk level of information, and the error rates of the prediction model with the input of data from 10 cases indicate that these ranges are all satisfied. In addition, when evaluated using the corresponding criteria, most of the results obtained using the construction cost estimation model developed in this study show accuracy comparable to the cost estimation accuracy ranges in Class 1-3. This finding indicates that in the early phase of a construction project, when the design information has not been confirmed and the availability of information to be utilized for construction cost estimation is highly limited, it is possible to develop a construction cost estimation model that can utilize the related information even if the LOD of the BIM setup that can be used in the architectural planning stage is relatively low compared with that in the subsequent phases of the project.