Chapter 2

Milk Production Forecasting by a Neuro-Fuzzy Model

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

Abstract

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).

Total Pages: 3-11 (9)

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