Evaluation using multilayer perception neural networks: a case study of undulatory median fin swimming in the knifefish Xenomystus nigri

Abstract

In this study, artificial intelligence, namely multilayer perception neural networks (MLP‐NN), was employed to predict the hydrodynamic performance of undulatory median fin propulsion in Xenomystus nigri. Good agreement was found between MLP‐NN predictions and actual mean thrust and power values calculated from elongated‐body theory. MLP‐NN has the ability to be a predictive tool for autonomous underwater vehicle design and hydrodynamic performance.