Application of Artificial Neural Network in Predicting the Electrical Conductivity of Recombined Milk

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NASERI H.; HAZBAVI I.; SHAHBAZI F.

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Journal: IRANIAN JOURNAL OF FOOD SCIENCE AND TECHNOLOGY Year:2020 | Volume:16 | Issue:96 Page(s): 65-77

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Title

Application of Artificial Neural Network in Predicting the Electrical Conductivity of Recombined Milk

Author(s)

NASERI H. | HAZBAVI I. | SHAHBAZI F. | Issue Writer Certificate

Keywords

Recombined milkQ1

Electrical conductivityQ2

ModelingQ2

Artificial neural networkQ2

Abstract

In this study, the Electrical conductivity of Recombined milk was modeled and predicted using Artificial neural networks (ANN) method. The protein (1, 2, 3 and 4%), lactose (4, 6, 8 and 10%), fat (3 and 6%) and temperature (50, 55, 60 and 65º C) were considered as the independent input parameters and Electrical conductivity of Recombined milk as the dependent parameter. Experimental data obtained from Electrical conductivity meter, were used for training and testing the network. In order to develop neural network firstly experimental data were randomly divided into three sets of training (70%), validating (15%) and testing model (15%). In order to develop ANN models. Multilayer perceptron networks (MLP) models were trained in two, three and four layers. The number of hidden layers and the number of neurons in each layer were obtained by trial and error. The best training algorithm was LM with the least MSE value. The highest coefficient of determination (R2) and lowest mean squared error (MSE) were considered as the criterion for selecting the best network. The network having three layers with a topology of 4-4-1 had the best results in predicting the Electrical conductivity of Recombined milk. This network has four neurons in the hidden layer. For this network, R2 and MSE were 0. 992 and 0. 011, respectively. These results can be used in milk processing factories. The correlation between the predicted and experimental values in the optimal topologies was higher than 99%.

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APA: Copy

NASERI, H., HAZBAVI, I., & SHAHBAZI, F.. (2020). Application of Artificial Neural Network in Predicting the Electrical Conductivity of Recombined Milk. IRANIAN JOURNAL OF FOOD SCIENCE AND TECHNOLOGY, 16(96 ), 65-77. SID. https://sid.ir/paper/72059/en

Vancouver: Copy

NASERI H., HAZBAVI I., SHAHBAZI F.. Application of Artificial Neural Network in Predicting the Electrical Conductivity of Recombined Milk. IRANIAN JOURNAL OF FOOD SCIENCE AND TECHNOLOGY[Internet]. 2020;16(96 ):65-77. Available from: https://sid.ir/paper/72059/en

IEEE: Copy

H. NASERI, I. HAZBAVI, and F. SHAHBAZI, “Application of Artificial Neural Network in Predicting the Electrical Conductivity of Recombined Milk,” IRANIAN JOURNAL OF FOOD SCIENCE AND TECHNOLOGY, vol. 16, no. 96 , pp. 65–77, 2020, [Online]. Available: https://sid.ir/paper/72059/en

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