A neural network based procedure for forecasting bovine semen motility

Abstract

We present a forecasting procedure based on a specially devised neural network aimed at computing a quality parameter of next semen batch of a given bull from the preceding time series of the same parameter. The procedure has its rationale in a sub symbolic issue of harmonic components analysis and appears more accurate than usual ARIMA systems on a limited bench of experiments.