Description

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.

Evolutionary Algorithms for Food Science and Technology

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Hardback by Evelyne Lutton , Nathalie Perrot

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Researchers and practitioners in food science and technology routinely face several challenges, related to sparseness and heterogeneity of data, as... Read more

    Publisher: ISTE Ltd and John Wiley & Sons Inc
    Publication Date: 13/12/2016
    ISBN13: 9781848218130, 978-1848218130
    ISBN10: 1848218133

    Number of Pages: 182

    Non Fiction , Technology, Engineering & Agriculture , Education

    Description

    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.

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