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@article{144781,
        author = {G.P.Gavane and D.B.Desai and V.P.Paramane},
        title = {Artificial Neural Network (ANN) Based Assistance System for Estimating Productivity of Construction Activities},
        journal = {International Journal of Innovative Research in Technology},
        year = {},
        volume = {4},
        number = {3},
        pages = {211-215},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=144781},
        abstract = {Construction can be considered as a dynamic industry which is constantly facing uncertainties. Factors affecting on productivity become an integral part of construction projects worldwide. A construction project is usually considered successful if it achieves good productivity. There are several factors due to which productivity varies. Therefore to achieve good productivity there is need to study on this various factors affecting on productivity and overcomes against the problem. The aim of this paper is to study of various Factors affecting on productivity   and the root causes of productivity quality variation on construction site in various cities & analyze them on the basis of discussion carried out with experts in locality.  The expand-focus principles & techniques will be applied for gathering the various causes from professional literature & also from local experts. The analysis helps to trace responsibility & improve the work process. After analyzing causes of construction cost overrun it will be easy to manage the project effectively so as to improve the quality of productivity. This study will provide a solution based on ANN for management of construction project to achieve optimum or good production quality for various construction projects in cities.},
        keywords = {Productivity, Construction Activity, Artificial Neural Network (ANN), Back Propagation Network (BPN) .},
        month = {},
        }