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

This paper focuses on modelling the electrical conductivity of recombined milk by artificial neural network (ANN). It aims to establish a non-linear relationship that accounts for the effect of milk constituents (protein, lactose, 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. In addition, log-sigmoid transfer function is proved to perform more practically than tan-sigmoid transfer function. The best ANN model has a 4-4-4-1 structure with log-sigmoid transfer function, After being trained for 4.4 x 10(5) epochs by back-propagation, the model produced a correlation coefficient of 0.9937 between the actual electrical conductivity (actual EC) and the modelled electrical conductivity (modelled EC) and a SSE of 0.4864. (C) 2001 Elsevier Science Ltd. All rights reserved.