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Modeling of thermodynamic properties of carrot product using ALO, GWO, and WOA algorithms under multi-stage semi-industrial continuous belt dryer.

Authors :
Kaveh, Mohammad
Amiri Chayjan, Reza
Taghinezhad, Ebrahim
Abbaspour Gilandeh, Yousef
Younesi, Abdollah
Rasooli Sharabiani, Vali
Source :
Engineering with Computers; Jul2019, Vol. 35 Issue 3, p1045-1058, 14p
Publication Year :
2019

Abstract

In this paper, multi-stage continuous belt (MSCB) dryer was used for carrot slices drying. Experiments were performed at three air speeds (1, 1.5, and 2 m/s) three belt linear velocities (2.5, 6.5, and 10.5 mm/s), and three air temperatures (40, 55, and 70 °C) in triplicate. Three intelligent systems including Ant-Lion-Optimizer (ALO), Grey-Wolf-Optimizer (GWO) and Whale-Optimization-Algorithm (WOA) models were developed to predict the thermodynamic properties of carrot slices including of effective moisture diffusivity (D<subscript>eff</subscript>) and specific energy consumption (SEC). The results revealed that D<subscript>eff</subscript> and SEC values were in the range of 1.77–2.90 × 10<superscript>−9</superscript> m<superscript>2</superscript>/s and 169.77–551.19 MJ/kg, respectively. The models of ALO, GWO, and WOA were able to predict the value of D<subscript>eff</subscript> and SEC. The amounts of correlation coefficient (R ), root-mean-square error (RMSE ), and mean absolute error (MAE ) for ALO, GWO, and WOA models for predication D<subscript>eff</subscript> were obtained (0.9989, 7.81 × 10<superscript>−12</superscript>, and 1.50 × 10<superscript>−12</superscript>), (0.9993, 5.39 × 10<superscript>−12</superscript>, and 1.03 × 10<superscript>−12</superscript>) and (0.9994, 4.95 × 10<superscript>−12</superscript>, and 9.54 × 10<superscript>−13</superscript>), respectively. In addition, The amounts of R , RMSE , and MAE for ALO, GWO, and WOA model for predication SEC were obtained (0.9983, 0.6700, and 0.1289), (0.9988, 0.5274, and 0.0715) and (0.9996, 0.2566, and 0.0060), respectively. Therefore, model of WOA can be used to easily and accurately predict D<subscript>eff</subscript> and SEC values. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
01770667
Volume :
35
Issue :
3
Database :
Complementary Index
Journal :
Engineering with Computers
Publication Type :
Academic Journal
Accession number :
136828452
Full Text :
https://doi.org/10.1007/s00366-018-0650-2