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Analyzing Cost and Time Objectives in the Construction Projects Using Artificial Neural Network

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The most important factor of success in every project is the level of achieving the cost and time objectives. The decision about the initiating of any new project is mostly made based on the estimated time and budget. To achieve an accurate estimation of cost and time in a project, criteria and success indicators should be defined properly to be used for the calculation of the required cost and time of the project. Therefore, by comparing the criteria and indicators in different projects, the decision-making process can be calibrated to improve the accuracy of the estimation process. In the present study, based on characteristics of different factors of projects related to time and cost and other criteria, a suitable formulation between time and cost ratio is presented. Also, using a smart method (artificial neural networks), a model for the prediction of the time and cost of the project is developed. The model can be applied in future projects based on available data of completed projects and optimized status of estimated time and cost can be observed.
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Construction Project Management; Estimating Project Budge; Scheduling Problem; Time-Cost Trade-Off; Artificial Neural Networks

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