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    Forecasting Construction Equipment Productivity Based on Weather Conditions: A Data-Driven Time-Series Machine Learning Approach

    Source: Journal of Management in Engineering:;2026:;Volume ( 042 ):;issue: 001::page 04025061-1
    Author:
    Assaf, Sena
    ,
    Sawma Awad, Johnny
    ,
    Srour, Issam
    DOI: 10.1061/JMENEA.MEENG-7068
    Publisher: American Society of Civil Engineers
    Abstract: AbstractAccurate forecasting of construction equipment productivity is crucial for effectively planning and controlling construction resources. Traditional approaches often rely on data from previous projects and the subjective experience of project ...
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      Forecasting Construction Equipment Productivity Based on Weather Conditions: A Data-Driven Time-Series Machine Learning Approach

    URI
    https://yetl.yabesh.ir/yetl1/handle/yetl/4312744
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    contributor authorAssaf, Sena
    contributor authorSawma Awad, Johnny
    contributor authorSrour, Issam
    date accessioned2026-08-20T11:50:28Z
    date available2026-08-20T11:50:28Z
    date copyright2025/11/11
    date issued2026
    identifier otherJMENEA.MEENG-7068.pdf
    identifier urihttp://yetl.yabesh.ir/yetl1/handle/yetl/4312744
    description abstractAbstractAccurate forecasting of construction equipment productivity is crucial for effectively planning and controlling construction resources. Traditional approaches often rely on data from previous projects and the subjective experience of project ...
    publisherAmerican Society of Civil Engineers
    titleForecasting Construction Equipment Productivity Based on Weather Conditions: A Data-Driven Time-Series Machine Learning Approach
    typeJournal Article
    journal volume42
    journal issue1
    journal titleJournal of Management in Engineering
    identifier doi10.1061/JMENEA.MEENG-7068
    journal fristpage04025061-1
    journal lastpage04025061-15
    page15
    treeJournal of Management in Engineering:;2026:;Volume ( 042 ):;issue: 001
    contenttypeFulltext
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