Modeling and Simulation of Apple Drying, Using Artificial Neural Network and Neuro -Taguchi’s Method | ||
| Journal of Agricultural Science and Technology | ||
| Article 6, Volume 11, Issue 5, 2009, Pages 559-571 PDF (350.38 K) | ||
| Authors | ||
| M. Mousavi* ; S. Javan | ||
| Department of Chemical Engineering, Faculty of Engineering, Ferdowsi University of Mashhad, Mashhad, Islamic Republic of Iran. | ||
| Abstract | ||
| Important parameters on apple drying process are investigated experimentally and modeled employing artificial neural network and neuro-Taguchi's method. Experimental results show that the apple drying curve stands in the falling rate period of drying. Temperature is the most important parameter that has a more pronounced effect on drying rate than the other two parameters i.e. air velocity and the thickness of apple slices. In order to model the drying process, a software was developed which uses the error back propagation algorithm for training. At first, the software was used to simulate the time-dependent variations of moisture content using neural network. Then in order to model the time derivation of moisture ratio in break point, the software was utilized in two ways. First, it was used with no use of any optimization method for modeling the process. In the other approach, the software in a hybrid fashion with Taguchi's method as an optimization method is utilized to correct weight matrix entries. The results demonstrate that the use of neuro-Taguchi's method can give some improvements over neural network accuracy as compared with conventional neural networks approach. By using neuro- Taguchi's method, error is reduced by about 46.4%. | ||
| Keywords | ||
| Modeling; simulation; Apple drying; artificial neural network; Neuro-Taguchi | ||
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