Estimation of scour depth around circular piers: applications of model tree
| Autor: | Dong-Sheng Jeng, Lisham Bonakdar, Amir Etemad-Shahidi |
|---|---|
| Rok vydání: | 2014 |
| Předmět: |
Pier
Atmospheric Science Engineering Artificial neural network business.industry Robust statistics Experimental data Structural engineering Geotechnical Engineering and Engineering Geology Field (computer science) Bridge (nautical) Tree (data structure) Hydraulic structure business Civil and Structural Engineering Water Science and Technology |
| Zdroj: | Journal of Hydroinformatics. 17:226-238 |
| ISSN: | 1465-1734 1464-7141 |
| DOI: | 10.2166/hydro.2014.151 |
| Popis: | Scour around bridge piers is one of the main causes of bridge failures and is of great importance for hydraulic engineers and scientists. Prediction of the scour depth around piers is complicated, and accurate results are rarely achieved by the existing models. Recently, data mining approaches such as artificial neural networks and fuzzy inference systems have been applied successfully to predict scour depth around hydraulic structures. In this study, an alternative robust data mining approach was used for the predictions of the scour depth around piers, and the results were compared with those of three empirical approaches. Performances of developed models were tested by experimental data sets collected in laboratory experiments and field measurements, together with existing empirical approaches. Statistical measures indicate that the proposed M5′ model provides a better prediction of scour depth than the empirical approaches. |
| Databáze: | OpenAIRE |
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