Machine Learning Cost Forecasting

Machine Learning Cost Forecasting is a computational forecasting method that leverages machine learning algorithms to predict future costs by identifying complex patterns and relationships in historical and contextual data, distinguishing it from traditional statistical or rule-based cost forecasting approaches through its adaptive, data-driven modeling capabilities.

82

Publications

3.3K

Citations

291

Authors

160

Institutions

Publications per year

2017–2026

71

Authors

291

  1. AS
    Ali Shehadeh

    Yarmouk University, Jordan

    2 publications · 214 citations

    2

    h-index

  2. RZ
    Rodrigo Zea-Vera

    Baylor College of Medicine, United States

    2 publications · 49 citations

    2

    h-index

  3. TK
    Todd K. Rosengart

    Baylor College of Medicine, United States

    2 publications · 49 citations

    2

    h-index

  4. HG
    Harshvardhan GM

    KIIT University, India

    2 publications · 46 citations

    2

    h-index

  5. FB
    Frank Bodendorf

    Friedrich-Alexander-Universität Erlangen-Nürnberg, Germany

    2 publications · 90 citations

    2

    h-index

1–5 of 291

Venues

  1. Mathematical Problems in Engineering

    MPE · 4 publications · 105 citations

    4

    h-index

  2. Computers & Industrial Engineering

    3 publications · 108 citations

    3

    h-index

  3. Procedia CIRP

    2 publications · 56 citations

    2

    h-index

  4. The Annals of Thoracic Surgery

    ATS · 2 publications · 49 citations

    2

    h-index

  5. 2

    h-index

1–5