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Volume 3 - Winter and Spring 2015                   ijmt 2015, 3 - Winter and Spring 2015: 33-40 | Back to browse issues page

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Sadat Hosseini A, Ganji H, Panahi R. Prediction of Mean Overtopping Discharge at Vertical Seawalls Using MLR and GLM Statistical Approaches. ijmt. 2015; 3 :33-40
URL: http://ijmt.ir/article-1-341-en.html
1- University of Tehran
2- Transportation Research Institute
3- Tarbiat modares University
Abstract:   (5362 Views)
Wave overtopping at breakwaters is one of their essential hydraulic characteristics when determining the design crest level. This study concentrates on developing a new practical formula on predicting wave overtopping, by implementing two different statistical models, Multiple Linear Regression model (MLR) and Generalized Linear Regression model (GLM). The models consider dependency of overtopping on a wide variety of quantities and yield to simple forms of prediction. Such statistical analysis are performed on a set of data called CLASH (Crest Level Assessment of Coastal Structures by full scale monitoring, neural network prediction and Hazard Analysis on permissible wave overtopping) the most complete and available database on overtopping phenomena. Proposed equations are compared with most recently extracted as well as successful ones. Comprehensive assessments clearly show more accurate predictions in the case of mean overtopping at vertical seawalls.
Full-Text [PDF 413 kb]   (1852 Downloads)    
Type of Study: Research Paper |
Received: 2014/07/11 | Accepted: 2015/01/13

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Creative Commons License This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.

Creative Commons License
International Journal of Maritime Technology is licensed under a

Creative Commons Attribution-NonCommercial 4.0 International License.