Application of Fractal Theory for Prediction of Shrinkage of Dried Kiwifruit Using Artificial Neural Network and Genetic Algorithm

被引：27

作者：

Fathi, Milad ^{[1
]}

Mohebbi, Mohebbat ^{[1
]}

Razavi, Seyed M. A. ^{[1
]}

机构：

[1] Ferdowsi Univ Mashhad, Dept Food Sci & Technol, Mashhad, Iran

来源：

DRYING TECHNOLOGY | 2011年 / 29卷 / 08期

关键词：

Artificial neural network; Dried kiwifruit; Fractal dimension; Genetic algorithm; Shrinkage; PHYSICAL-PROPERTIES; MOISTURE-CONTENT; OPTIMIZATION; DEHYDRATION; METHODOLOGY; MODEL; ANN;

D O I：

10.1080/07373937.2011.553755

中图分类号：

TQ [化学工业];

学科分类号：

0817 ;

摘要：

In current research, fractal theory has been applied for estimation of shrinkage of osmotically dehydrated and air-dried kiwifruit using a combination of neural network and genetic algorithm. Kiwifruits were dehydrated at different conditions and digital images of final dried products were taken. Kiwifruit-background interface lines were detected using a threshold combined with an edge detection approach and their corresponding fractal dimensions were calculated based on a box counting method. A neural network was constructed using fractal dimension and moisture content as inputs to predict shrinkage of dried kiwifruit and a genetic algorithm was applied for optimization of the neural network's parameters. The results indicated good accuracy of optimal model (correlation coefficient of 0.95) and high potential application of fractal theory and described intelligent model for shrinkage estimation of dried kiwifruit.

引用

页码：918 / 925

页数：8

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