期刊
EXPERT SYSTEMS WITH APPLICATIONS
卷 38, 期 5, 页码 5591-5602出版社
PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.eswa.2010.10.076
关键词
Artificial neural network; Ascorbic acid; Kinetic; Asparagus offcinalis L; Thermal treatments
An artificial neural network was developed to predict the kinetics of ascorbic acid loss in green asparagus during thermal treatments and the model was trained using a back-propagation algorithm. The results indicate that the optimal ANN models consisted one hidden layer and the optimal number of neurons in the hidden layer was 24, 26, 26 and 18 for bud, upper, middle and butt segments of asparagus, respectively. The ANNs could predict the kinetic parameters of ascorbic acid degradation in asparagus with an MSE of 1.3925 and MAE 0.5283 for bud segment, MSE 2.4618 and MAE 0.6436 for upper segment. MSE 0.8985 and 0.4258 for middle segment and MSE 0.2707 and MAE 0.1883 for butt segment. In addition, the correlation coefficients between experimental k, t(1/2) or D-value and predicted values were greater than 0.99 in all cases. Therefore, ANN offers a simple, quick and convenient means of the kinetic parameters prediction in chemical kinetics. (C) 2010 Elsevier Ltd. All rights reserved.
作者
我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。
推荐
暂无数据