Evolutionary algorithms for food science and technology:
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 optimiz...
Gespeichert in:
| Beteilige Person: | |
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| Weitere beteiligte Personen: | , |
| Format: | Elektronisch E-Book |
| Sprache: | Englisch |
| Veröffentlicht: |
London, UK Hoboken, NJ
ISTE, Ltd. ;
2016
London, UK Hoboken, NJ Wiley 2016 |
| Schriftenreihe: | Metaheuristics set
v. 7 |
| Schlagwörter: | |
| Links: | https://learning.oreilly.com/library/view/-/9781848218130/?ar |
| Zusammenfassung: | 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. |
| Beschreibung: | Includes bibliographical references and index. - Print version record |
| Umfang: | 1 Online-Ressource (200 Seiten) |
| ISBN: | 9781119136828 1119136822 1119136849 9781119136842 1848218133 9781848218130 |
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| 520 | |a 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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| spelling | Lutton, Evelyne VerfasserIn aut Evolutionary algorithms for food science and technology Evelyne Lutton, Nathalie Perrot, Alberto Tonda London, UK Hoboken, NJ ISTE, Ltd. ; 2016 London, UK Hoboken, NJ Wiley 2016 1 Online-Ressource (200 Seiten) Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Metaheuristics set v. 7 Includes bibliographical references and index. - Print version record 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. Food industry and trade Mathematical models Evolutionary computation Réseaux neuronaux à structure évolutive COMPUTERS ; Computer Engineering TECHNOLOGY & ENGINEERING ; Food Science Food industry and trade ; Mathematical models Perrot, Nathalie MitwirkendeR ctb Tonda, Alberto MitwirkendeR ctb 1848218133 Erscheint auch als Druck-Ausgabe 1848218133 |
| spellingShingle | Lutton, Evelyne Evolutionary algorithms for food science and technology Food industry and trade Mathematical models Evolutionary computation Réseaux neuronaux à structure évolutive COMPUTERS ; Computer Engineering TECHNOLOGY & ENGINEERING ; Food Science Food industry and trade ; Mathematical models |
| title | Evolutionary algorithms for food science and technology |
| title_auth | Evolutionary algorithms for food science and technology |
| title_exact_search | Evolutionary algorithms for food science and technology |
| title_full | Evolutionary algorithms for food science and technology Evelyne Lutton, Nathalie Perrot, Alberto Tonda |
| title_fullStr | Evolutionary algorithms for food science and technology Evelyne Lutton, Nathalie Perrot, Alberto Tonda |
| title_full_unstemmed | Evolutionary algorithms for food science and technology Evelyne Lutton, Nathalie Perrot, Alberto Tonda |
| title_short | Evolutionary algorithms for food science and technology |
| title_sort | evolutionary algorithms for food science and technology |
| topic | Food industry and trade Mathematical models Evolutionary computation Réseaux neuronaux à structure évolutive COMPUTERS ; Computer Engineering TECHNOLOGY & ENGINEERING ; Food Science Food industry and trade ; Mathematical models |
| topic_facet | Food industry and trade Mathematical models Evolutionary computation Réseaux neuronaux à structure évolutive COMPUTERS ; Computer Engineering TECHNOLOGY & ENGINEERING ; Food Science Food industry and trade ; Mathematical models |
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