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Resumen del producto
Whitehead, D.A., F., Galván-Magaña, J.T., Ketchum, E.M., Hoyos-Padilla, R., González-Armas, F., Pancaldi & D., Olivier
(2020).
The use of machine learning to detect a foraging behaviour in whale sharks: A new tool in conservation.
Journal of Fish Biology.
98(3): 865-869.
DOI: 10.1111/jfb.14589.
The use of machine learning to detect a foraging behaviour in whale sharks: A new tool in conservation
Darren A. Whitehead, Felipe Galván-Magaña, James T. Ketchum, Edgar M. Hoyos-Padilla, Rogelio González-Armas, Francesca Pancaldi y Damien Olivier
In this study we present the first attempt at modelling the feeding behaviour of whale sharks using a machine learning analytical method. A total of eight sharks were monitored with tri-axial accelerometers and their foraging behaviours were visually observed. Our results highlight that the random forest model is a valid and robust approach to predict the feeding behaviour of the whale shark. In conclusion this novel approach exposes the practicality of this method to serve as a conservation tool and the capability it offers in monitoring potential disturbances of the species.
Palabras clave: acceleration data logger; biologging tool; endangered species; shark conservation
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