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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| Main Authors: | Reza Lotfi, Soheila Sadeghi, Sadia Samar Ali, Fatemeh Ramyar, Ehsan Ghafourian, Ebrahim Farbod |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Wiley
2025-06-01
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| Series: | Engineering Reports |
| Subjects: | |
| Online Access: | https://doi.org/10.1002/eng2.70161 |
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