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Predicting maximum scour depth around bridge abutment using M5 model
Scour around piers and abutments leads to a lot of bridge failures. Scouring around the bridge piers and abutments is one of the most important factors in bridge failure which happens over time and increases during floods, probably causing general damage to the bridge. Accordingly, the accurate estimation of scouring around the bridge piers and abutments can help engineers to take steps to deal with bridge destructions. Recently, data-driven models have been used widely to estimate the scour depth around bridge piers and abutments. Najafzadeh, Barani and Hessami-Kermani (2015) used a set of data-driven models such as the gravitational search algorithm and the particle swarm optimization algorithm to estimate the scour around bridge abutments. Sediment particles size, geometric characteristics of bridge abutment and approach flow conditions were considered as effective parameters on scouring mechanism. The results of this research showed that data-driven models can estimate the scour depth with high accuracy. In the present study, M5 tree model has been used to predict maximum scour depth around bridge abutment. High accuracy, simplicity and understandability are considered the advantages of this algorithm. A huge amount of data from credible references have been used to build and validate the tree model.
Predicting maximum scour depth around bridge abutment using M5 model
Scour around piers and abutments leads to a lot of bridge failures. Scouring around the bridge piers and abutments is one of the most important factors in bridge failure which happens over time and increases during floods, probably causing general damage to the bridge. Accordingly, the accurate estimation of scouring around the bridge piers and abutments can help engineers to take steps to deal with bridge destructions. Recently, data-driven models have been used widely to estimate the scour depth around bridge piers and abutments. Najafzadeh, Barani and Hessami-Kermani (2015) used a set of data-driven models such as the gravitational search algorithm and the particle swarm optimization algorithm to estimate the scour around bridge abutments. Sediment particles size, geometric characteristics of bridge abutment and approach flow conditions were considered as effective parameters on scouring mechanism. The results of this research showed that data-driven models can estimate the scour depth with high accuracy. In the present study, M5 tree model has been used to predict maximum scour depth around bridge abutment. High accuracy, simplicity and understandability are considered the advantages of this algorithm. A huge amount of data from credible references have been used to build and validate the tree model.
Predicting maximum scour depth around bridge abutment using M5 model
Javad Zahiri (author) / Seyed Mahmood Kashefipour (author)
2018
Article (Journal)
Electronic Resource
Unknown
Metadata by DOAJ is licensed under CC BY-SA 1.0
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