Proceedings of the 2016 Conference on Information Technologies in Science, Management, Social Sphere and Medicine

An Integrated ANN-GA Approach to Data Classification

Authors
Stanislav Alkhasov, Alexander Tselykh, Alexey Tselykh
Corresponding Author
Stanislav Alkhasov
Available Online May 2016.
DOI
https://doi.org/10.2991/itsmssm-16.2016.2How to use a DOI?
Keywords
classification, artificial neural networks, genetic algorithms, ANN-GA
Abstract
In this paper, we present an advanced approach to data classification based on the integration of artificial neural networks (ANNs) and genetic algorithms (GAs). We modify neural network architecture in a two-stage process. During the first stage, GA finds a suboptimal neural network architecture: number of nodes, training algorithm, learning rate, etc. Then, the fitting of weight coefficients and bias is carried out in order to minimize GA fitness function. In final section of the paper, we compare the results of the conventional and the proposed approaches.
Open Access
This is an open access article distributed under the CC BY-NC license.

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Proceedings
Information Technologies in Science, Management, Social Sphere and Medicine
Part of series
Advances in Computer Science Research
Publication Date
May 2016
ISBN
978-94-6252-196-4
DOI
https://doi.org/10.2991/itsmssm-16.2016.2How to use a DOI?
Open Access
This is an open access article distributed under the CC BY-NC license.

Cite this article

TY  - CONF
AU  - Stanislav Alkhasov
AU  - Alexander Tselykh
AU  - Alexey Tselykh
PY  - 2016/05
DA  - 2016/05
TI  - An Integrated ANN-GA Approach to Data Classification
BT  - Information Technologies in Science, Management, Social Sphere and Medicine
PB  - Atlantis Press
UR  - https://doi.org/10.2991/itsmssm-16.2016.2
DO  - https://doi.org/10.2991/itsmssm-16.2016.2
ID  - Alkhasov2016/05
ER  -