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.

Standort
Deutsche Nationalbibliothek Frankfurt am Main
Umfang
Online-Ressource
Sprache
Englisch

Erschienen in
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)

Urheber
Kotliarov, Eugene
Petrushina, Tatyana

DOI
10.2478/s13537-014-0206-5
URN
urn:nbn:de:101:1-2410301457526.485640019897
Rechteinformation
Open Access; Der Zugriff auf das Objekt ist unbeschränkt möglich.
Letzte Aktualisierung
15.08.2025, 07:35 MESZ

Datenpartner

Dieses Objekt wird bereitgestellt von:
Deutsche Nationalbibliothek. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.

Beteiligte

  • Kotliarov, Eugene
  • Petrushina, Tatyana

Ähnliche Objekte (12)