Drying of jujube ('zizyphus jujube mill') fruit: comparison of prediction from mathematical models and artificial neural networks
作者： Barat Ghobadian , Ali Motevali , Ahmad Abbaszadeh , Gholam Hassan Najafi , Saeid Minaei
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摘要: In this study, the application of artificial neural networks (ANNs) and mathematical models for hot-air drying Jujube fruit is presented. Air velocity, temperature time were used to predict moisture ratio (MR) rate (DR) variations. Assessment seven revealed that Midilli model exhibited best performance in fitting experimental data (R2=0.9996, RMSE= 0.005112 x2=2.61E-05). Using some data, an ANN, trained by standard backpropagation algorithm, was developed. The ANN able variations MR DR quite well with determination coefficients (R2) 0.9997, 0.9993 0.9996 training, validation testing, respectively. prediction mean square error obtained as 0.001, 0.0011 0.0013 Results show good agreement between on one hand other. However, network modeling yielded a better jujube compared all studied.
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