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首页> 外文期刊>Engineering with Computers >Modeling of thermodynamic properties of carrot product using ALO, GWO, and WOA algorithms under multi-stage semi-industrial continuous belt dryer
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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

机译:多级半工业连续式带式烘干机中使用ALO,GWO和WOA算法的胡萝卜产品热力学性质的建模

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摘要

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 2m/s) three belt linear velocities (2.5, 6.5, and 10.5mm/s), and three air temperatures (40, 55, and 70 degrees 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-eff) and specific energy consumption (SEC). The results revealed that D-eff and SEC values were in the range of 1.77-2.90x10(-9)m(2)/s and 169.77-551.19MJ/kg, respectively. The models of ALO, GWO, and WOA were able to predict the value of D-eff 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-eff were obtained (0.9989, 7.81x10(-12), and 1.50x10(-12)), (0.9993, 5.39x10(-12), and 1.03x10(-12)) and (0.9994, 4.95x10(-12), and 9.54x10(-13)), 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-eff and SEC values.
机译:在本文中,使用多级连续带(MSCB)干燥器用于胡萝卜切片干燥。在三个空气速度(1,1.5和2m / s)三带线速度(2.5,6.5和10.5mm / s)中进行实验,以及三次空气温度(40,55和70℃)的三份。开发了三种智能系统,包括蚂蚁优化器(ALO),灰狼优化器(GWO)和鲸优化算法(WOA)模型,以预测胡萝卜切片的热力学性质,包括有效的水分扩散率(D-EFF )和特定的能量消耗(秒)。结果表明,D-EFF和SEC值分别为1.77-2.90x10(-9)m(2)/ s和169.77-551.19mJ / kg。 ALO,GWO和WOA的模型能够预测D-EFF和SEC的价值。获得了用于预测D-EFF的ALO,GWO和WOA模型的相关系数(R),根均方误差(RMSE)和平均绝对误差(MAE)的量(0.9989,7.81x10(-12)和1.50x10(-12)),(0.9993,5.39x10(-12)和1.03x10(-12))和(0.9994,4.95x10(-12)和9.54x10(-13)))。此外,获得了用于预测SEC的ALO,GWO和WOA模型的R,RMSE和MAE的量(0.9983,0.6700和0.1289),(0.9988,0.5274和0.0715)和(0.9996,0.2566和0.0060 ), 分别。因此,WOA的模型可用于容易和准确地预测D-EFF和SEC值。

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