نوع مقاله : مقاله پژوهشی
نویسندگان
1 کارشناسی ارشد دانشگاه آیت الله بروجردی
2 دانشیار گروه عمران دانشگاه آیت الله بروجردی
چکیده
کلیدواژهها
موضوعات
عنوان مقاله [English]
نویسندگان [English]
Extended Abstract
Background and Objective
Bridge foundation erosion is one of the main causes of bridge destruction worldwide. It is also one of the most important issues in bridge safety. The complex nature of bridge base scour and the effects of various parameters on its estimation further highlight the necessity of using a comprehensive and nonlinear model. In this study, an attempt has been made to examine deci-sion tree models for measuring the scour depth of bridge foundations and to make a comparison between these methods.
Methodology
The present study uses four decision tree-based models and data (and information) from multiple bridges. The information used in this study to model the decision trees include up-stream flow velocity, average bed particle diameter, upstream flow depth and base width, angle of water intrusion into the base, base length, and diameter of particles of which 84% are smaller than its diameter, base shape factor, as input variables and local scour depth as output in the model. In this study, new decision tree methods are used to calculate and compare the bridge base scour depth. In this study, data from the US Federal Highway Administration was used to build models and validate decision trees. It was extracted from statistics on a number of bridges in the US. All information was collected in the field and includes information related to the depth of scour around bridge piers in different locations.
Findings
The results show that the Extreme Gradient Boosting (XGB) and Random Forest (RF) mod-els with coefficients of determination of 0.76 and 0.73 had higher accuracy than the four mod-els examined, and the Gradient Boosting (GB) model was in the second place after these two models with coefficients of determination of 0.67, and the Decision Tree (DT) model was in the last place. Also, with the sensitivity analysis performed on the models, it was observed that the base width and the base length have the greatest effect on the scour depth. After these two pa-rameters, the upstream flow depth has the greatest effect on the scour depth.
Conclusion
Bridge foundation scour is one of the most important issues in bridge safety. Considering the importance of this issue, in the present study, an attempt has been made to use new decision tree-based models to evaluate this issue. Decision tree methods are one of the best evaluation methods due to their simple understanding and ability to work with large and complex data. In future study, it is possible to combine new decision tree-based methods with other data mining or machine learning methods. The results show that the Extreme Gradient Boosting (XGB) and Random Forest (RF) models had higher accuracy than the four models examined, and the Gra-dient Boosting (GB) model and the Decision Tree (DT) model was in the last place. Also, with the sensitivity analysis performed on the models, it was observed that the base width and the base length have the greatest effect on the scour depth. After these two parameters, the up-stream flow depth has the greatest effect on the scour depth.
کلیدواژهها [English]
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