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  • 标题:Cascade Artificial Neural Network Models for Predicting Shelf Life of Processed Cheese
  • 本地全文:下载
  • 作者:Goyal, Gyanendra Kumar ; Goyal, Sumit
  • 期刊名称:Journal of Advances in Information Technology
  • 印刷版ISSN:1798-2340
  • 出版年度:2013
  • 卷号:4
  • 期号:2
  • 页码:80-83
  • DOI:10.4304/jait.4.2.80-83
  • 语种:English
  • 出版社:Academy Publisher
  • 摘要:The purpose of this study is to develop artificial neural network (ANN) models for predicting shelf life of processed cheese stored at 7-8ºC. Body & texture, aroma & flavour, moisture and free fatty acids were taken as input parameters, and sensory score as output parameter for developing the models. The developed Cascade single layer ANN models were compared with each other. Bayesian regularization was used for training ANN models. Network was trained with 100 epochs, and neurons in each hidden layer(s) varied from 3 to 20. Cascade ANN models very well predicted the shelf life of processed cheese.
  • 关键词:Artificial Intelligence;Cascade;Artificial neural networks (ANN);Processed Cheese;Shelf Life;Soft Computing
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