A Robust, Resilience Machine Learning With a Risk Approach for Project Scheduling

ABSTRACT This study proposes a novel Robust, Resilient, and Risk‐Based approach in Machine Learning (3RML) that emphasizes the application of project scheduling for the first time. A robust stochastic LASSO regression model is proposed to predict project duration. This model seeks to enhance a tradi...

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書誌詳細

主要な著者:	Reza Lotfi, Soheila Sadeghi, Sadia Samar Ali, Fatemeh Ramyar, Ehsan Ghafourian, Ebrahim Farbod
フォーマット:	Artigo
言語:	Inglês
出版事項:	Wiley 2025-06-01
シリーズ:	Engineering Reports
主題:	machine learning project scheduling resiliency risk robust optimization
オンライン･アクセス:	https://doi.org/10.1002/eng2.70161
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