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...
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Main Authors: | , , |
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Format: | Book |
Language: | English |
Published: |
London
John Wiley & Sons
2016
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Series: | COMPUTER ENGINEERING SERIES : METAHAURISTICS SET
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Subjects: | |
Online Access: | Click Here to View Status and Holdings. |
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020 | # | # | |a 9781848218130 |q hardback |
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041 | 0 | # | |a eng |
090 | 0 | 0 | |a TP372.8 |b .L88 2016 |
100 | 1 | # | |a Lutton, Evelyne |e author |
245 | 1 | 0 | |a Evolutionary Algorithms for Food Science and Technology |c Evelyne Lutton, Nathalie Perrot, Alberto Tonda |
264 | # | 1 | |a London |b John Wiley & Sons |c 2016 |
264 | # | 4 | |c 2016 |
300 | # | # | |a 148 pages |b illustrations |c 23 cm |
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490 | 1 | # | |a COMPUTER ENGINEERING SERIES : METAHAURISTICS SET |
500 | # | # | |a Includex index |
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. |
650 | # | # | |a Food industry and trade |x Automation |
700 | 0 | # | |a Perrot, Nathalie |e author |
700 | 0 | # | |a Tonda, Alberto |e author |
856 | 4 | 0 | |z Click Here to View Status and Holdings. |u https://opac.uitm.edu.my/opac/detailsPage/detailsHome.jsp?tid=800654 |
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