Research Topics in Agricultural and Applied Economics

Volume: 3

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The aim of this e-book series is to publish high quality economic research in agricultural and applied economics. It particularly fosters quantitative studies which make original contribution on ...
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Milk Production Forecasting by a Neuro-Fuzzy Model

Pp. 3-11 (9)

Atsalakis S. George, Parasyri G. Maria and Zopounidis D. Constantinos


Many fields are increasingly applying Neuro-fuzzy techniques such as in model identification and forecasting of linear and non-linear systems. This chapter presents a neuro-fuzzy model for forecasting milk production of two producers. The model utilizes a time series of daily data. The milk forecasting model is based on Adaptive Neural Fuzzy Inference System (ANFIS). ANFIS uses a hybrid learning technique that combines the least-squares method and the back propagation gradient descent method to estimate the optimal milk forecast parameters. The results indicate the superiority of ANFIS model when compared with two conventional models: an Autoregressive (AR) and an Autoregressive Moving Average model (ARMA).


Milk forecasting, neuro-fuzzy, ANFIS, AR, ARMA, forecasting, milk production.


Department of Production Engineering and Management, Technical University of Crete, 73100 Chania, Crete, Greece