Risk-Informed Prediction of Dredging Project Duration Using Stochastic Machine Learning
Dredging engineering projects are complex because they involve greater uncertainty from the natural environment, social needs, government policy and many stakeholders. Engineering companies submit tenders that draw on similar cases undertaken in recent years. However, weather, earthquakes, typhoons...
Main Authors: | Jui-Sheng Chou, Ji-Wei Lin |
---|---|
Format: | Article |
Language: | English |
Published: |
MDPI AG
2020-06-01
|
Series: | Water |
Subjects: | |
Online Access: | https://www.mdpi.com/2073-4441/12/6/1643 |
Similar Items
-
Establishing Control Limits on Time Performance Indicators of Projects through Monte Carlo Simulation and Earned Duration Management
by: Akbar Alam-Tabriz, et al.
Published: (2019-06-01) -
Dredging - 1967-1973/
by: 342145 Kahler, R. C., et al.
Published: (1973) -
Applying Machine Learning to Estimate the Effort and Duration of Individual Tasks in Software Projects
by: Andre O. Sousa, et al.
Published: (2023-01-01) -
Dredging and dredged material disposal /
by: Montgomery, Raymond L., et al.
Published: (1984) -
Maintenance dredging for waterway channel /
by: Mohd. Aiful Amir Awang Noh, 1988-, et al.
Published: (2011)