Artificial neural network modelling of the electrical conductivity property of recombined milk

This paper focuses on modelling the electrical conductivity of recombined m ilk by artificial neural network (ANN). It aims to establish a non-linear r elationship that accounts for the effect of milk constituents (protein, lac tose, and fat) and temperature on the electrical conductivity of recombined milk. Various ANNs of 3-layer and 4-layer were investigated. Compared with 3-layer ANN models, 4-layer ANN models provide better model performance. I n addition, log-sigmoid transfer function is proved to perform more practic ally than tan-sigmoid transfer function. The best ANN model has a 4-4-4-1 s tructure with log-sigmoid transfer function, After being trained for 4.4 x 10(5) epochs by back-propagation, the model produced a correlation coeffici ent of 0.9937 between the actual electrical conductivity (actual EC) and th e modelled electrical conductivity (modelled EC) and a SSE of 0.4864. (C) 2 001 Elsevier Science Ltd. All rights reserved.