Title A Study on the Development of Construction Budget Estimating Model for Public Office Buildings based on Artificial Neural Network
Authors Kim, Hyeon Jin ; Kim, Han Soo
DOI https://dx.doi.org/10.6106/KJCEM.2023.24.5.022
Page pp.22-34
ISSN 2005-6095
Keywords Construction Cost Prediction Model; Construction Budget Estimating; Public Building Projects; Artificial Neural Network
Abstract Predicting accurately the construction cost budget in the early stages of construction projects is crucial to support the client's decision-making and achieve the objectives of the construction project. This holds true for public construction projects as well. However, the current methods for predicting construction cost budgets in the early stages of public construction projects are not sophisticated enough in terms of accuracy and reliability, indicating a need for improvement. The objective of this study is to develop a construction cost budget prediction model that can be utilized in the early stages of public building projects using an artificial neural network (ANN). In this study, an artificial neural network model was developed using the SPSS Statistics program and the data provided by the Public Procurement Service. The level of construction cost budget prediction was analyzed, and the accuracy of the model was validated through additional testing. The validation results demonstrated that the developed artificial neural network model exhibited an error range for estimates that can be utilized in the early stages of projects, indicating the potential to predict construction cost budgets more accurately by incorporating various project conditions.