Weight loss prediction model gor pig carcass based on a genetic algorithm back-propagation neural network

C. Sun, L. Chen, Y. Li, H. Yao, N. Zhang, C. Li, G. Zhou, Y. Chen

研究成果: 雜誌貢獻期刊論文同行評審

摘要

Because the weight loss of a pig carcass in the spray-chilling process is easily affected by the spraying frequency and duration, a prediction model for weight loss based on a genetic algorithm (GA) back-propagation (BP) neural network is proposed in this article. With three-way crossbred pig carcasses selected as the test materials, the duration and time interval of high-frequency spraying, the duration and time interval of low-frequency spraying, and the duration of a single spray were selected as inputs to the network model. The weight and threshold of the network were then optimized by the GA. The prediction model for pig carcass weight loss established by the GA BP neural network yielded a correlation coefficient of R = 0.99747 between the network output value of the test samples and the target value. Weight loss prediction by the model is feasible and allows better expression of the nonlinear relationship between weight loss and the main controlling factors. The results can be a reference for chilled meat production.

原文英語
頁(從 - 到)1071-1077
頁數7
期刊Transactions of the ASABE
63
發行號4
DOIs
出版狀態已發佈 - 2020

ASJC Scopus subject areas

  • Forestry
  • Food Science
  • Biomedical Engineering
  • Agronomy and Crop Science
  • Soil Science

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