Khabat Khosravi, Aitazaz A. Farooque, Sayed M. Bateni, Changhyun Jun, Dorsa Mohammadi, Zahra Kalantari, James R. Cooper
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Abstract
The potential of advanced tree-based models and optimized deep learning algorithms to predict fluvial bedload transport was explored, identifying the most flexible and accurate algorithm, and the o...
期刊介绍：
The aim of Engineering Applications of Computational Fluid Mechanics is a continuous and timely dissemination of innovative, practical and industrial applications of computational techniques to solve the whole range of hitherto intractable fluid mechanics problems. The journal is a truly interdisciplinary forum and publishes original contributions on the latest advances in numerical methods in fluid mechanics and their applications to various engineering fields including aeronautic, civil, environmental, hydraulic and mechanical. The journal has a distinctive and balanced international contribution, with emphasis on papers addressing practical problem-solving by means of robust numerical techniques to generate precise flow prediction and optimum design, and those fostering the thorough understanding of the physics of fluid motion. It is an open access journal.
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