Neural Network Interpretation of Bayesian Logical-Probabilistic Fuzzy Inference Model

Gulnara Kozhomberdieva, Dmitry Burakov, Georgii Khamchichev

2022

Abstract

The paper discusses the possibilities of using the Bayesian logical-probabilistic model of fuzzy inference, previously proposed, researched and software implemented by the authors, in a neural network context. A multilayer structure of a neuro-fuzzy network based on a Bayesian logic-probabilistic model is presented. According to the authors, the proposed network structure is comparable to the well-known Takagi–Sugeno– Kang and Wang–Mendel neuro-fuzzy networks. An example shows which network parameters can be used to train it.

Paper Citation

in Harvard Style

Kozhomberdieva G., Burakov D. and Khamchichev G. (2022). Neural Network Interpretation of Bayesian Logical-Probabilistic Fuzzy Inference Model. In Proceedings of the 3rd International Symposium on Automation, Information and Computing - Volume 1: ISAIC; ISBN 978-989-758-622-4, SciTePress, pages 50-56. DOI: 10.5220/0011901700003612

in Bibtex Style

@conference{isaic22,
author={Gulnara Kozhomberdieva and Dmitry Burakov and Georgii Khamchichev},
title={Neural Network Interpretation of Bayesian Logical-Probabilistic Fuzzy Inference Model},
booktitle={Proceedings of the 3rd International Symposium on Automation, Information and Computing - Volume 1: ISAIC},
year={2022},
pages={50-56},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0011901700003612},
isbn={978-989-758-622-4},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 3rd International Symposium on Automation, Information and Computing - Volume 1: ISAIC
TI - Neural Network Interpretation of Bayesian Logical-Probabilistic Fuzzy Inference Model
SN - 978-989-758-622-4
AU - Kozhomberdieva G.
AU - Burakov D.
AU - Khamchichev G.
PY - 2022
SP - 50
EP - 56
DO - 10.5220/0011901700003612
PB - SciTePress