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Artificial Neural Networks in Food Processing
Modeling and Predictive Control
Language:
English
Published/Copyright:
2021
About this book
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.
- Discusses theory and current applications of ANNs in food processing technology.
- A valuable tool for students and researchers in food science.
- Code available for download.
Author / Editor information
Mohamed Tarek Khadir, University Badji Mokhtar of Annaba, Algeria.
Supplementary Materials
Topics
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Frontmatter
I -
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Acknowledgement
VII -
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Contents
IX -
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Introduction
XV -
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1 Biological inspiration and single artificial neurons
1 -
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2 Artificial neural networks for food processes: a survey
27 -
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3 Multi-layered perceptron
51 -
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4 Radial basis function networks
81 -
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5 Self-organising feature maps or Kohonen maps
95 -
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6 Deep artificial neural networks
117 -
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7 Overview of model predictive control theory and applications in food science using ANN
145 -
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Index
179
Publishing information
Pages and Images/Illustrations in book
eBook published on:
January 18, 2021
eBook ISBN:
9783110646054
Paperback published on:
January 18, 2021
Paperback ISBN:
9783110645941
Pages and Images/Illustrations in book
Front matter:
18
Main content:
182
Illustrations:
45
Coloured Illustrations:
34
Tables:
25
Audience(s) for this book
Advanced Students, Early Career Starters, Researchers and Engineers in Food Processing Industry.
Safety & product resources
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Manufacturer information:
Walter de Gruyter GmbH
Genthiner Straße 13
10785 Berlin
productsafety@degruyterbrill.com
