A Novel Approach to Weighted Fuzzy Rules for Positive Samples

Martina Daňková

2022

Abstract

In this contribution, we propose a novel approach to automated fuzzy rule base generation based on underlying observational data. The core of this method lies in adding information to a particular fuzzy rule in the form of attached weight given as a value extracted from a relational data model. In particular, we blend two approaches to receive particular models that overcome their specific drawbacks.

Paper Citation

in Harvard Style

Daňková M. (2022). A Novel Approach to Weighted Fuzzy Rules for Positive Samples. In Proceedings of the 14th International Joint Conference on Computational Intelligence (IJCCI 2022) - Volume 1: FCTA; ISBN 978-989-758-611-8, SciTePress, pages 209-216. DOI: 10.5220/0011548800003332

in Bibtex Style

@conference{fcta22,
author={Martina Daňková},
title={A Novel Approach to Weighted Fuzzy Rules for Positive Samples},
booktitle={Proceedings of the 14th International Joint Conference on Computational Intelligence (IJCCI 2022) - Volume 1: FCTA},
year={2022},
pages={209-216},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0011548800003332},
isbn={978-989-758-611-8},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 14th International Joint Conference on Computational Intelligence (IJCCI 2022) - Volume 1: FCTA
TI - A Novel Approach to Weighted Fuzzy Rules for Positive Samples
SN - 978-989-758-611-8
AU - Daňková M.
PY - 2022
SP - 209
EP - 216
DO - 10.5220/0011548800003332
PB - SciTePress