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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Add Tag | Summary: | 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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| Item Description: | Includex index |
| Physical Description: | 148 pages illustrations 23 cm |
| ISBN: | 9781848218130 |
Automation in the food industry