A hybrid intelligence approach to enhance the prediction accuracy of local scour depth at complex bridge piers

• Main Authors: Bui, D. T., Shirzadi, A., Amini, A., Shahabi, H., Al-Ansari, N., Hamidi, S., Singh, S. K., Pham, B. T., Ahmad, B. B., Ghazvinei, P. T.
• Format: Article
• Language: English
• Published: MDPI AG 2020
• Subjects: TA Engineering (General). Civil engineering (General)
• Online Access: http://eprints.utm.my/id/eprint/86878/1/DieuTienBui2020_AHybridIntelligenceApproach.pdf; http://eprints.utm.my/id/eprint/86878/; https://dx.doi.org/10.3390/su12031063
• Institution: Universiti Teknologi Malaysia

Local scour depth at complex piers (LSCP) cause expensive costs when constructing bridges. In this study, a hybrid artificial intelligence approach of random subspace (RS) meta classifier, based on the reduced error pruning tree (REPTree) base classifier, namely RS-REPTree, was proposed to predict t...