Elektrik Elektronik Mühendisliği Bölümü Yayın Koleksiyonu

Permanent URI for this collectionhttps://hdl.handle.net/20.500.12416/411

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    Citation - WoS: 14
    Citation - Scopus: 20
    A Machine Learning Study To Enhance Project Cost Forecasting
    (Elsevier, 2022) Narbaev, Timur; Hazir, Oncu; Inan, Tolga
    In project management it is critical to obtain accurate cost forecasts using effective methods. This study presents a Machine Learning model based on Long-Short Term Memory to forecast the project cost. The model uses the seven-dimensional feature vector, including schedule and cost performance factors and their moving averages as a predictor. Based on the cost variation patterns from the training phase, we validate the model using three hundred experiments in the testing phase. Overall, the proposed model produces more accurate cost estimates when compared to the traditional Earned Value Management index-based model. Copyright (C) 2022 The Authors.