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Synthesizing of models for identification of teletraffic Markov chains by artificial neural networks and decision tree method Cover

Synthesizing of models for identification of teletraffic Markov chains by artificial neural networks and decision tree method

Journal of Electrical Engineering
Volume 69 (2018): Issue 5 (September 2018)
By: Ivelina Stefanova Balabanova,  Georgi Ivanov Georgiev,  Stanimir Michaylov Sadinov and  Stela Savova Kostadinova  
Open Access
|Dec 2018

Authors

Ivelina Stefanova Balabanova

ivstoeva@abv.bg

Technical University of Gabrovo, Faculty of Electrical Engineering and Electronics, Department of Communications Equipment and Technologies, Gabrovo city, Bulgaria

Georgi Ivanov Georgiev

givanow@abv.bg

Technical University of Gabrovo, Faculty of Electrical Engineering and Electronics, Department of Communications Equipment and Technologies, Gabrovo city, Bulgaria

Stanimir Michaylov Sadinov

sadinov.tc@abv.bg

Technical University of Gabrovo, Faculty of Electrical Engineering and Electronics, Department of Communications Equipment and Technologies, Gabrovo city, Bulgaria

Stela Savova Kostadinova

stela.kostadinova@tu-varna.bg

Technical University of Varna, Faculty of Electronics, Department of Communications Engineering and Technologies, Varna, Bulgaria
DOI: https://doi.org/10.2478/jee-2018-0055 | Journal eISSN: 1339-309X | Journal ISSN: 1335-3632
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Language: English
Page range: 379 - 384
Submitted on: Jul 10, 2018
|
Published on: Dec 14, 2018
Published by: Slovak University of Technology in Bratislava
In partnership with: Paradigm Publishing Services
Publication frequency: 6 issues per year
Keywords:
Markov chain,
artificial neural network,
decision tree,
synthesized models,
telegraphic identification
Related subjects:
Engineering,
Introductions and overviews,
Engineering, other

© 2018 Ivelina Stefanova Balabanova, Georgi Ivanov Georgiev, Stanimir Michaylov Sadinov, Stela Savova Kostadinova, published by Slovak University of Technology in Bratislava
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

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