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. Num Pages: 182 pages. BIC Classification: TDCT. Category: (P) Professional & Vocational. Dimension: 241 x 164 x 15. Weight in Grams: 426. . 2015. 1st Edition. Hardcover. . . . . Books ship from the US and Ireland.

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Bibliographic Details

Title: Evolutionary Algorithms for Food Science and Technology
Publisher: ISTE Ltd and John Wiley & Sons Inc
Publication Date: 2016
Language: English
ISBN 10: 1848218133
ISBN 13: 9781848218130
Binding: Hardcover
Condition: New

About this title

Synopsis

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.

About the Author

Evelyne Lutton, INRA.

Nathalie Perrot, INRA.

Alberto Tonda, INRA.

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