Estimation of tomato drying parameters using artificial neural networks
| Autor: | M. Mokhtarian, F. Koushki |
|---|---|
| Jazyk: | perština |
| Rok vydání: | 2012 |
| Předmět: | |
| Zdroj: | Pizhūhish va Nuāvarī dar ̒Ulūm va Sanāyi̒-i Ghaz̠āyī, Vol 1, Iss 1, Pp 61-74 (2012) |
| Druh dokumentu: | article |
| ISSN: | 2252-0937 2538-2357 |
| DOI: | 10.22101/jrifst.2012.05.21.116 |
| Popis: | In this research we have simulated drying tomato thin layer by hot air convection. Tomato slices were dried in two temperatures 60° and 70℃. Perceptron neural network was used to predict moisture ratio and drying rate of samples during the drying process. Best neural network topology for ANN-I based on one hidden layer 2 and 8 neuron per hidden layers for moisturizing ratio and the drying rate obtained respectively. Furthermore, best neural network topology for ANN-II based on one hidden layer 11 neuron for moisturizing ratio and the drying arte obtained. Generally, the results showed that ANN-II had preferable result to predict drying parameters of drying tomato. |
| Databáze: | Directory of Open Access Journals |
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