neuro-fuzzy and response surface modeling of osmotic dehydration of pomegranate arils
نویسندگان
چکیده
in this research, pomegranate arils are dehydrated by osmotic dehydration in 40, 50, and 60 % sucrose solutions and at 45, 55 and 65 degrees c and weight reduction, solids grain and water loss of the products were measured at 60, 120 and 180 minutes of process. osmotic dehydration processes was modeled by combination of neural network and fuzzy logic techniques (neuro-fuzzy) and response surface methodology. for modeling, interpolation and increase of the data’s, fuzzy logic was used. by entering the obtained results from fuzzy model into the neural network tool, the feed-forward-back-propagation network with the topology of 3-8-3 and the correlation coefficient of 0.98344 and mean square error of 0.02278 with application of log-sigmoid transfer function (logsig) and levenberg–marquardt learning algorithm was determined as the best neural model. regression models created by response surface methodology by correlation coefficient of 0.90 were also capable for prediction of response factors but in comparison with neuro-fuzzy models have a lower accuracy.
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عنوان ژورنال:
مهندسی بیوسیستم ایرانجلد ۴۷، شماره ۲، صفحات ۲۴۳-۲۵۵
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