Milk Production estimates using feed forward artificial neural networks

Abstract

The accuracy of milk production forecasts on dairy farms using a ffann (feed forward artificial neural network) with polynomial post-processing, is reported. Historical milk production data was used to derive models that are able to predict milk production from farm inputs, using a standard ffann, a ffann with polynomial post-processing and multiple linear regression. Forecasts obtained from the models were then compared with each other. Within the scope of the available data, it was found that the standard ffann did not improve on the multiple regression technique, but the ffann with polynomial post processing did.