Prediction of Dredging Productivity Using a Rock and Soil Classification Model
Publication: Journal of Waterway, Port, Coastal, and Ocean Engineering
Volume 141, Issue 4
Abstract
The prediction of dredging productivity plays an important role in controlling the costs and optimizing the scheduling of the dredging process. However, it is very difficult to achieve satisfactory forecasting efficiency because there are so many uncertain variables, including the rock, soil, and water properties; the main performance index of the dredger; and environmental restrictions. In this paper, the authors have developed a quantitative classification model for dredging materials under complex conditions, in which the weight of the condition attributes is calculated using rough-set theory and conditional entropy. Then, by considering the effect of the rock and soil conditions, the main performance index of the dredger, and the influence of the underwater environment, a prediction model for dredger production efficiency was developed. This approach is applied to a land reclamation project in Tianjin, China. In the study case, the efficiency of the dredger production is predicted fairly well when compared with the realistic conditions, so this model provides a feasible method and a technical tool for dredging cost control and schedule planning.
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Acknowledgments
This research is supported by the National Basic Research Program of China (No. 2013CB035904), the Innovative Research Groups of the National Natural Science Foundation of China (No. 51321065), and the National Science Foundation of China (No. 51339003).
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Published In
Journal of Waterway, Port, Coastal, and Ocean Engineering
Volume 141 • Issue 4 • July 2015
Copyright
© 2015 American Society of Civil Engineers.
History
Received: Jun 16, 2014
Accepted: Jan 20, 2015
Published online: Apr 7, 2015
Published in print: Jul 1, 2015
Discussion open until: Sep 7, 2015
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