A hybrid intelligence approach to enhance the prediction accuracy of local scour depth at complex bridge piers
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...
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| 主要な著者: | , , , , , , , , , |
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| フォーマット: | 論文 |
| 言語: | English |
| 出版事項: |
MDPI AG
2020
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| 主題: | |
| オンライン･アクセス: | 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 |
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