Food science applications and international trends of artificial neural networks
Recently, research has been focusing increasingly on the system of artificial neural networks, and its results are used in many places by industrial practices. The success of these networks lies in their ability to recognize the complex relationships and patterns in data, as well as to predict unkno...
Elmentve itt :
| Szerzők: | |
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| Dokumentumtípus: | Cikk |
| Megjelent: |
WESSLING Nemzetközi Kutató és Oktató Központ Közhasznú Nonprofit Kft.
Budapest
2018
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| Sorozat: | Élelmiszervizsgálati közlemények
64 No. 3 |
| Kulcsszavak: | Élelmiszertudomány |
| Tárgyszavak: | |
| Online Access: | http://acta.bibl.u-szeged.hu/79235 |
| Tartalmi kivonat: | Recently, research has been focusing increasingly on the system of artificial neural networks, and its results are used in many places by industrial practices. The success of these networks lies in their ability to recognize the complex relationships and patterns in data, as well as to predict unknown samples, thus enabling value and category predictions with high certainty. Artificial neural networks are very efficient tools for modeling non-linear trends within data. In many cases, they perform well where traditional statistical tools provide unsatisfactory results or unable to solve a given research problem. In our work, the operation principle and structure (topol-ogy) of artificial neural networks are summarized, as well as the classification and application possibilities of the networks. The latest food science applications are presented separately, based on the usage type (prediction, classification, optimiza-tion). Results show that artificial neural networks possess many beneficial properties, making them especially suitable for solving food science tasks. |
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| Terjedelem/Fizikai jellemzők: | 2154-2163 |
| ISSN: | 0422-9576 |