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Evolutionary algorithms for food science and technology / Evelyne Lutton, Nathalie Perrot, Alberto Tonda.
- Format:
- Book
- Author/Creator:
- Lutton, Evelyne, author.
- Perrot, Nathalie, author.
- Tonda, Alberto, author.
- Series:
- Computer engineering series (London, England). Metaheuristics set ; Volume 7.
- Metaheuristics Set ; Volume 7
- Language:
- English
- Subjects (All):
- Evolutionary programming (Computer science).
- Genetic algorithms.
- Food industry and trade--Data processing.
- Food industry and trade.
- Physical Description:
- 1 online resource (187 pages) : illustrations.
- Place of Publication:
- London, England ; Hoboken, New Jersey : ISTE : Wiley, 2016.
- Summary:
- Researchers and practitioners in food science and technology routinely face several challenges, related to sparseness and heterogeneity of data, as well as to the uncertainty in the measurements and the introduction of expert knowledge in the models. Evolutionary algorithms (EAs), stochastic optimization techniques loosely inspired by natural selection, can be effectively used to tackle these issues. In this book, we present a selection of case studies where EAs are adopted in real-world food applications, ranging from model learning to sensitivity analysis.
- Notes:
- Includes bibliographical references and index.
- Description based on online resource; title from PDF title page (ebrary, viewed February 9, 2017).
- ISBN:
- 9781119136842
- 1119136849
- 9781119136835
- 1119136830
- 9781119136828
- 1119136822
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