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    Arctic tern-optimized weighted feature regression system for predicting bridge scour depth by Jui-Sheng Chou, Asmare Molla

    Published 2024-12-01
    “…This paper presents a pioneering artificial intelligence (AI) solution – the Arctic Tern-Optimized Weighted Feature Least Squares Support Vector Regression (ATO-WFLSSVR) system to aid civil engineers in accurately predicting scour depth at bridges. This prediction system amalgamates the strengths of hybrid models by uniting a metaheuristic optimization algorithm with weighted features and least squares support vector regression (WFLSSVR). …”
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