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Veuillez utiliser cette adresse pour citer ce document : http://hdl.handle.net/1834/60

Titre: Analysis and prediction of yellowfin tuna (Thunnus albacares) catch rates of longline fisheries in the western Indian Ocean using a neural network.
Auteur(s): Nishida, T.
Komatsu, T.
Date de publication: 1998
Référence bibliographique: IOTC Proceedings, 7th Expert Consultation on Indian Ocean Tunas. p. 241-250
Description: Strengthening tuna management is one of the primary tasks for the new Indian Ocean Tuna Commission (IOTC). Stock assessment and the prediction of the dynamics of the tuna resources will become increasingly important research topics because they provide the basic information for the management decision process. Under these circumstances, this paper attempts to develop the stock analyses and prediction techniques using neural networks. As a first step and as a test study, analyses and predictions of catch rates of the Japanese yellowfin tuna longline fisheries are attempted.
URI/URL: http://hdl.handle.net/1834/60
Collection(s) :Proceedings - Expert Consultation on Indian Ocean Tunas

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