title: Artificial neural networks as a classification method in the behavioural sciences.
abstract: The classification and recognition of individual characteristics and behaviours constitute a preliminary step and is an important objective in the behavioural sciences. Current statistical methods do not always give satisfactory results. To improve performance in this area, we present a methodology based on one of the principles of artificial neural networks: the backpropagation gradient. After summarizing the theoretical construction of the model, we describe how to parameterize a neural network using the example of the individual recognition of vocalizations of four fallow deer (Dama dama). With 100% recognition and 90% prediction success, the results are very promising.
authors.affiliation: Institut de Recherche sur les Grands Mammifères, I.N.R.A., B.P. 27, 31326 Castanet-Tolosan Cedex France.
authors.forename: D
authors.initials: D
authors.lastname: Reby
authors.affiliation: CNRS UMR 5576 CESAC, Bat 4R3, Université Paul Sabatier, 118 route de Narbonne, 31062 Toulouse Cedex France.
authors.forename: S
authors.initials: S
authors.lastname: Lek
authors.affiliation: CNRS UMR 5552 LET, Bat 4R3, Université Paul Sabatier, 118 route de Narbonne, 31062 Toulouse Cedex France.
authors.forename: I
authors.initials: I
authors.lastname: Dimopoulos
authors.affiliation: Institut de Recherche sur les Grands Mammifères, I.N.R.A., B.P. 27, 31326 Castanet-Tolosan Cedex France.
authors.forename: J
authors.initials: J
authors.lastname: Joachim
authors.affiliation: CNRS UMR 5552 LET, Bat 4R3, Université Paul Sabatier, 118 route de Narbonne, 31062 Toulouse Cedex France.
authors.forename: J
authors.initials: J
authors.lastname: Lauga
authors.affiliation: Institut de Recherche sur les Grands Mammifères, I.N.R.A., B.P. 27, 31326 Castanet-Tolosan Cedex France.
authors.forename: S
authors.initials: S
authors.lastname: Aulagnier