Hybrid neural network for classification problem solving
Abstract: In this article we investigate some approaches to the artificial neural networks training with use of hybrid algorithms. Algorithms which are based on the back propagation algorithm and the ant colony algorithm are considered in detail. The article describes the application of the artificial neural network with the authors’ hybrid training algorithm. The preliminary studies have shown that the algorithm improves the efficiency of the problems on standard test databases. The application of the algorithm for practical problems solution in the field of medicine, namely the definition of danger level determination of tuberculosis carriers is described. It was shown that the accuracy of the hybrid algorithm is up to 22% higher than of the classical one.
- Location
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Deutsche Nationalbibliothek Frankfurt am Main
- Extent
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Online-Ressource
- Language
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Englisch
- Bibliographic citation
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Hybrid neural network for classification problem solving ; volume:4 ; number:2 ; year:2014 ; pages:86-94 ; extent:9
Open computer science ; 4, Heft 2 (2014), 86-94 (gesamt 9)
- Creator
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Kotliarov, Eugene
Petrushina, Tatyana
- DOI
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10.2478/s13537-014-0206-5
- URN
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urn:nbn:de:101:1-2410301457526.485640019897
- Rights
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Open Access; Der Zugriff auf das Objekt ist unbeschränkt möglich.
- Last update
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15.08.2025, 7:35 AM CEST
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Associated
- Kotliarov, Eugene
- Petrushina, Tatyana
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