prediction of paddy moisture content during thin layer drying using machine vision and artificial neural networks

intelligent real time prediction of moisture content using artificial neural network in pistachio thin layer drying

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prediction of papaya fruit moisture content using hybrid gmdh - neural network modeling during thin layer drying process

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 ...

Thin Layer Drying and Equilibrium Moisture Content Equations for Canola (Brassica napus L.)

A fully instrumented air conditioning laboratory unit capable of controlling drying air temperature and humidity integrated with an instantaneous weighing thin layer drying system was used to investigate the thin layer drying behavior and desorption equilibrium moisture content of canola (Brassica napus L.). To this aim, freshly harvested canola samples with moisture content of about 12±0.5% (d...

modeling thin-layer drying of banana and process optimization using artificial neural network

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Prediction of Gas Lift Parameters Using Artificial Neural Networks

scour modeling piles of kambuzia industrial city bridge using hec-ras and artificial neural network

today, scouring is one of the important topics in the river and coastal engineering so that the most destruction in the bridges is occurred due to this phenomenon. whereas the bridges are assumed as the most important connecting structures in the communications roads in the country and their importance is doubled while floodwater, thus exact design and maintenance thereof is very crucial. f...