intelligent real time prediction of moisture content using artificial neural network in pistachio thin layer drying
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prediction of paddy moisture content during thin layer drying using machine vision and artificial neural networks
the goal of this study was to predict the moisture content of paddy using machine vision and artificial neural networks (anns). the grains were dried as thin layer with air temperatures of 30, 40, 50, 60, 70, and 80°c and air velocities of 0.54, 1.18, 1.56, 2.48 and 3.27 ms-1. kinetics of l*a*b* were measured. the air temperature, air velocity, and l*a*b* values were used as ann inputs. the res...
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in this work, a hybrid gmdh–neural network model was developed in order to predict the moisture content of papaya slices during hot air drying in a cabinet dryer. for this purpose, parameters including drying time, slices thickness and drying temperature were considered as the inputs and the amount of moisture ratio (mr) was estimated as the output. exactly 50% of the data points were used for ...
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Prediction of Time of Capillary Rise in Porous Media Using Artificial Neural Network (ANN)
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عنوان ژورنال:
فرآوری و نگهداری مواد غذاییجلد ۲، شماره ۲، صفحات ۱۷-۳۲
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