Estimation of approximate costs and contract prices of public school buildings with a deterministic approach

In this study, a method is proposed for the preliminary estimation of school building costs. For this purpose, the projects of 96 school buildings, which were put out to tender by public institutions and the result announcement was published, were provided from the Electronic Public Procurement Platform (EKAP). These projects are divided into 81 training data and 15 test data. The construction cost of educational buildings through projects may affect the output vectors; "Number of Classrooms, Construction Duration, Total Number of Floors, Floor Height, Building Height, Building Height Class, Basement Height, Earthquake Design Class, Floor Class, Ground Safety Stress, Bed Coefficient, Concrete Class, Number of Elevators, Wet Area, Raft Foundation Height, Floor Area, Basement Area, Total Area" input vector parameters were determined and used in modeling and analysis. Analyzes were carried out with "SPSS Statistics 26" software. Regression Analyzes (RA) were performed using these parameters, and 14 regression models in total for 28 regression models were developed for both the Contract Price and the Approximate Cost in order to estimate the costs of the educational buildings. Approximate Cost Prices and Contract Prices were tried to be estimated in the healthiest and closest to the real value with the developed models. The model in which 16 parameters were used with the created equations was the model with the best correlation level with the determination coefficient R²=0.914 for the Approximate Cost Price and R²=0.900 for the Contract Price. An error rate of 11.70% was found between the approximate cost estimates obtained using the model and the actual costs. It was determined that there was a 13.10% error between the estimated contract prices and the actual contract prices. The Durbin-Watson criterion was used to check the consistency between predicted results and actual results. As a result, an approach that can estimate the approximate costs and contract prices of school buildings of different types and coefficients with error rates lower than 20% has been created. Both public institutions and contracting construction companies will be able to make realistic cost estimates by benefiting from these modeling, providing time savings. Conducting similar studies by increasing the number of data may be a solution to minimize the error rate in subsequent modeling.