PREDICTING THE REALIZATION OF PROJECT GOALS (TIME-COST) ON CONSTRUCTION PROJECTS BASED ON THE ACQUIRED VALUE TECHNIQUE
In this study, in order to evaluate the correct performance of project management to control time and cost, which will be effective in managing other project elements, control of cost and time of project implementation was considered one of the most important factors for project success. Be. In this case, using this technique, the value gained, the project performance was evaluated up to a specific time period, project problems were identified and appropriate decisions were made to improve the project process. Also, using the parameters and performance indicators of this technique, time And the final cost of the project was predicted. In general, this study shows that the proposed model can provide more accurate and stable prediction results. Given the better performance of neural-fuzzy networks than neural networks and the acquired value technique, we conclude that neural-fuzzy networks due to their ability to solve complex and poorly structured problems and use data from multiple projects, can be Help managers to make better decisions.