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Data-Driven Machine Learning Models for a Multi-Objective Flapping Fin Unmanned Underwater Vehicle Control System
Recent work has explored the use of time-series neural network surrogate models to predict thrust from vehicle design and fin kinematics.
Evaluation of Surrogate Models for Multi-fin Flapping Propulsion Systems
The aim of this study is to develop surrogate models for quick, accurate prediction of thrust forces generated through flapping fin propulsion for given operating conditions and fin geometries.
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