A Novel Approach to Weighted Fuzzy Rules for Positive Samples

Martina Daňková

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Paper

A Novel Approach to Weighted Fuzzy Rules for Positive Samples

Topics: Approximate Reasoning; Fuzzy Approaches to Information Retrieval; Fuzzy Control; Fuzzy Information Processing; Fuzzy Methods in Data Analysis

In Proceedings of the 14th International Joint Conference on Computational Intelligence - Volume 1: FCTA, 209-216, 2022 , Valletta, Malta

Author: Martina Daňková

Affiliation: University of Ostrava, CE IT4Innovations, 30. dubna 22, 701 03 Ostrava 1,Czech Republic

Keyword(s): Fuzzy Relation, Relational Model, Fuzzy Approximation, Implicative Model, Fuzzy IF–THEN Rules.

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.

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Paper citation in several formats:

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) - FCTA; ISBN 978-989-758-611-8; ISSN 2184-3236, SciTePress, pages 209-216. DOI: 10.5220/0011548800003332

@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) - FCTA},
year={2022},
pages={209-216},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0011548800003332},
isbn={978-989-758-611-8},
issn={2184-3236},
}

TY - CONF

JO - Proceedings of the 14th International Joint Conference on Computational Intelligence (IJCCI 2022) - FCTA
TI - A Novel Approach to Weighted Fuzzy Rules for Positive Samples
SN - 978-989-758-611-8
IS - 2184-3236
AU - Daňková, M.
PY - 2022
SP - 209
EP - 216
DO - 10.5220/0011548800003332
PB - SciTePress