Artificial Neural Networks in Food Processing : : Modeling and Predictive Control / / Mohamed Tarek Khadir.

• Superior document: Title is part of eBook package: De Gruyter DG Ebook Package English 2021
• VerfasserIn: Khadir, Mohamed Tarek,
• Place / Publishing House: Berlin ;, Boston : : De Gruyter, , [2021]; ©2021
• Year of Publication: 2021
• Language: English
• Series: De Gruyter STEM
• Physical Description: 1 online resource (XVIII, 182 p.)
• Other title: Frontmatter --; Acknowledgement --; Contents --; Introduction --; 1 Biological inspiration and single artificial neurons --; 2 Artificial neural networks for food processes: a survey --; 3 Multi-layered perceptron --; 4 Radial basis function networks --; 5 Self-organising feature maps or Kohonen maps --; 6 Deep artificial neural networks --; 7 Overview of model predictive control theory and applications in food science using ANN --; Index
• Format: Mode of access: Internet via World Wide Web.
• ISBN: 9783110646054; 9783110750720; 9783110750706; 9783110754001; 9783110753776; 9783110754162; 9783110753936
• DOI: 10.1515/9783110646054
• Access: restricted access
• Hierarchical level: Monograph
• Statement of Responsibility: Mohamed Tarek Khadir.

Artificial Neural Networks (ANNs) is a powerful computational tool to mimic the learning process of the mammalian brain. This book gives a comprehensive overview of ANNs including an introduction to the topic, classifications of single neurons and neural networks, model predictive control and a review of ANNs used in food processing. Also, examples of ANNs in food processing applications such as pasteurization control are illustrated.