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    Satellite-Inspired Time-Frequency Deep Learning for Predicting and Assessing Financial Health in General Contractors

    Source: Journal of Construction Engineering and Management:;2026:;Volume ( 152 ):;issue: 008::page 04026120-1
    Author:
    Cheng, Min-Yuan
    ,
    Khitam, Akhmad F. K.
    ,
    Vu, Quoc-Tuan
    ,
    Widjaja, Daniel Darma
    DOI: 10.1061/JCEMD4.COENG-18108
    Publisher: American Society of Civil Engineers
    Abstract: AbstractThe ability to accurately predict and evaluate financial health is crucial for project owners and stakeholders to ensure stability and minimize risk. Traditional models such as the Altman Z-score, while widely used, adapt poorly to rapidly ...
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      Satellite-Inspired Time-Frequency Deep Learning for Predicting and Assessing Financial Health in General Contractors

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    https://yetl.yabesh.ir/yetl1/handle/yetl/4311207
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    • Journal of Construction Engineering and Management

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    contributor authorCheng, Min-Yuan
    contributor authorKhitam, Akhmad F. K.
    contributor authorVu, Quoc-Tuan
    contributor authorWidjaja, Daniel Darma
    date accessioned2026-08-20T10:44:56Z
    date available2026-08-20T10:44:56Z
    date copyright2026/05/31
    date issued2026
    identifier otherJCEMD4.COENG-18108.pdf
    identifier urihttp://yetl.yabesh.ir/yetl1/handle/yetl/4311207
    description abstractAbstractThe ability to accurately predict and evaluate financial health is crucial for project owners and stakeholders to ensure stability and minimize risk. Traditional models such as the Altman Z-score, while widely used, adapt poorly to rapidly ...
    publisherAmerican Society of Civil Engineers
    titleSatellite-Inspired Time-Frequency Deep Learning for Predicting and Assessing Financial Health in General Contractors
    typeJournal Article
    journal volume152
    journal issue8
    journal titleJournal of Construction Engineering and Management
    identifier doi10.1061/JCEMD4.COENG-18108
    journal fristpage04026120-1
    journal lastpage04026120-16
    page16
    treeJournal of Construction Engineering and Management:;2026:;Volume ( 152 ):;issue: 008
    contenttypeFulltext
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