Estimating project duration based on cost in public projects

The construction sector, as one of the fastest growing ve most critical sectors worldwide, is faced with great challenges in project policies ve cost estimations. Especially in public projects, considering the importance of budget ve time management becomes a great necessity in accurate duration estimation. This can be done by examining the data obtained from public projects in Turkey, Australia, Nigeria, Texas ve other regions, with cost-based duration estimation methods. In addition to traditional approaches such as linear regression ve Bromilow model, artificial intelligence techniques, especially artificial neural networks (ANN), will be used to perform estimations. It is anticipated that artificial neural networks will provide more accurate results compared to the traditional distribution in complex units between cost ve duration. As a result, more effective use of ANN will be contributed to calculating estimated amounts during the duration of projects. Thus, the completion of public projects can be estimated better ve more effectively, ve the efficient use of public resources can be increased.