Artificial neural networks as a classification method in the behavioural sciences

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.