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Evolutionary Algorithms for Food Science and Technology (Computer Engineering: Metaheuristics Set, 7) - Hardcover
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.
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About the Author
Evelyne Lutton, INRA.
Nathalie Perrot, INRA.
Alberto Tonda, INRA.
"About this title" may belong to another edition of this title.
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Evolutionary Algorithms for Food Science and Technology
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Evolutionary Algorithms for Food Science and Technology
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ISTE Ltd and John Wiley and Sons Inc, GB, 2016
ISBN 10: 1848218133
ISBN 13: 9781848218130
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Hardback. Condition: New. 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. Seller Inventory # LU-9781848218130
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Evolutionary Algorithms for Food Science and Technology (Hardcover)
Published by
ISTE Ltd and John Wiley & Sons Inc, London, 2016
ISBN 10: 1848218133
ISBN 13: 9781848218130
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Hardcover. Condition: new. Hardcover. 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. 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. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. Seller Inventory # 9781848218130
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Evolutionary Algorithms for Food Science and Technology (Computer Engineering: Metaheuristics Set, 7)
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Evolutionary Algorithms for Food Science and Technology (Computer Engineering: Metaheuristics Set, 7)
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