Artificial Neural Network Models for Predicting the Energy Consumption of the Process of Crystallization Syrup in Konya Sugar Factory
Journal Title: International Journal of Intelligent Systems and Applications in Engineering - Year 2017, Vol 5, Issue 1
Abstract
In this study, artificial neural network models have been developed from the sugar production process stages in Konya Sugar Factory using artificial neural networks to estimate the energy consumption of the process of crystallization syrup. Models developing specific enthalpy, mass and pressure as input layer parameters and consumption energy as output layer were used. 124 different data are taken from Konya Sugar Factory during January 2016. Feedforward back propagation algorithm was used in the training phase of the network. Learning function LEARNGDM and the number of hidden layer kept constant as 2 and transfer functions are modified. In the developed 27 ANN model, 2-5-1 network architecture was determined as the best suitable network architecture and transfer function is determined logsig function as the optimal transfer function. Optimum results of the model taken in the coefficient of determination was found R = 0.98 neural network training, testing and validate was also found to be R = 0.98, the performance of the network for not shown data to network was found R=0,99.
Authors and Affiliations
Abdullah Erdal Tümer*| Necmettin Erbakan University, Dept.of Comp. Eng., Konya,Turkey, Bilgen Ayan Koç| Necmettin Erbakan University, Dept.of Industry Eng., Konya,Turkey, Sabri Koçer| Necmettin Erbakan University, Dept.of Comp. Eng., Konya,Turkey
Keywords
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- EP ID EP816
- DOI 10.18201/ijisae.2017526691
- Views 434
- Downloads 25
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