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首页> 外文期刊>Drying Technology: An International Journal >Application of Fractal Theory for Prediction of Shrinkage of Dried Kiwifruit Using Artificial Neural Network and Genetic Algorithm
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Application of Fractal Theory for Prediction of Shrinkage of Dried Kiwifruit Using Artificial Neural Network and Genetic Algorithm

机译:分形理论在人工猕猴桃干缩预测中的应用

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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.View full textDownload full textKeywordsArtificial neural network, Dried kiwifruit, Fractal dimension, Genetic algorithm, ShrinkageRelated var addthis_config = { ui_cobrand: "Taylor & Francis Online", services_compact: "citeulike,netvibes,twitter,technorati,delicious,linkedin,facebook,stumbleupon,digg,google,more", pubid: "ra-4dff56cd6bb1830b" }; Add to shortlist Link Permalink http://dx.doi.org/10.1080/07373937.2011.553755
机译:在当前的研究中,分形理论已被应用到结合神经网络和遗传算法的渗透脱水和风干猕猴桃的收缩率估计中。猕猴桃在不同条件下脱水,并拍摄最终干燥产品的数字图像。使用阈值结合边缘检测方法检测奇异果-背景界面线,并基于盒计数法计算其对应的分形维数。使用分形维数和水分含量作为输入来构建神经网络,以预测干奇异果的收缩,并应用遗传算法优化神经网络的参数。结果表明,最优模型的正确性(相关系数为0.95)和分形理论的潜在应用潜力很高,并描述了用于干猕猴桃收缩率估计的智能模型。 var addthis_config = {ui_cobrand:“泰勒和弗朗西斯在线”,servicescompact:“ citeulike,netvibes,twitter,technorati,delicious,linkedin,facebook,stumbleupon,digg,google,更多”,发布号:“ ra-4dff56cd6bb1830b”};添加到候选列表链接永久链接http://dx.doi.org/10.1080/07373937.2011.553755

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