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Drying kinetics and ANN modeling of paneer at low pressure superheated steam

机译:低压过热蒸汽下窗格玻璃的干燥动力学和ANN模型

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摘要

Drying characteristics, selection of analytical model and development of artificial neural network (ANN) models of 1 cm3 paneer at low pressure superheated steam drying (LPSSD) were studied. Effects of steam temperature and pressure on drying rates were determined. Page’s model was selected as the best predictive model. Second degree polynomial, non linear regression analysis resulted in a good agreement of defined model by changing the values of temperature and corresponding pressure. Optimized ANN models were developed for all data set. The correlation coefficient for all data set was >0.98 in all cases.
机译:研究了低压过热蒸汽干燥(LPSSD)1 cm 3 窗格玻璃的干燥特性,分析模型的选择以及人工神经网络(ANN)模型的发展。确定蒸汽温度和压力对干燥速率的影响。佩奇的模型被选为最佳预测模型。通过改变温度和相应的压力值,二阶多项式,非线性回归分析得出了定义模型的良好一致性。针对所有数据集开发了优化的人工神经网络模型。在所有情况下,所有数据集的相关系数均> 0.98。

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