An evolutionary deep neural network for predicting morbidity of gastrointestinal infections by food contamination

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• 作者：Qin Song^aAuthor Vitae ; Yu-Jun Zheng^b ; ^{yujun.zheng@computer.org}Author Vitae ; Yu Xue^cAuthor Vitae ; Wei-Guo Sheng^bAuthor Vitae ; Mei-Rong Zhao^aAuthor Vitae
• 关键词：Morbidity prediction ; Gastrointestinal infections ; Deep denoising autoencoder (DDAE) ; Neural networks ; Evolutionary algorithms (EAs)
• 刊名：Neurocomputing
• 出版年：2017
• 出版时间：22 February 2017
• 年：2017
• 卷：226
• 期：Complete
• 页码：16-22
• 全文大小：1484 K
• 卷排序：226

文摘

A deep neural network is developed predicting gastrointestinal morbidity. An evolutionary algorithm is proposed for training the network. A higher prediction accuracy is obtained on a real-world dataset.