Predicting age and maturity of endangered Spiny butterfly ray, Gymnura altavela (Linnaues 1758) ‎‎‎using artificial neural network ‎‎(multilayer perceptron)‎

Abstract

The data were derived from several sources, including 338 records of maturity, age, and disc width of the Spiny butterfly ray (Gymnura altavela). ‎An artificial neural network ‎‎(Multilayer Perceptron) model (1, 10, 2) was used to predict the maturity and age of the ‎ Spiny butterfly ray, which is a high-accurate ‎model with excellent efficiency. This network ‎shortens the time, effort and cost compared to traditional methods or a convolutional neural ‎network (CNN) in age prediction. Therefore, we can predict the maturity and age of ‎individuals without killing or harming them, just by getting simple data (disc width) and ‎inter it into the updated model from the network. This network allows us to obtain valuable ‎data for use in studying stock indicators of ‎endangered Spiny butterfly ray ‎without ‎compromising their factual ‎stock.‎