Fuzzy quantifier-based fuzzy rough sets

• Autorzy: Theerens Adnan , Cornelis Chris

Identyfikatory

DOI

10.15439/2022F231

• Konferencja: Federated Conference on Computer Science and Information Systems (17 ; 04-07.09.2022 ; Sofia, Bulgaria)
• Języki publikacji: EN

Abstrakty

EN

In this paper we apply vague quantification to fuzzy rough sets to introduce fuzzy quantifier based fuzzy rough sets (FQFRS), an intuitive generalization of fuzzy rough sets. We show how several existing models fit in this generalization as well as how it inspires novel models that may improve these existing models. In addition, we introduce several new binary quantification models. Finally, we introduce an adaptation of FQFRS that allows seamless integration of outlier detection algorithms to enhance the robustness of the applications based on FQFRS.

Słowa kluczowe

EN

computer science; adaptation model; computational modelling; rough set; robustness; computational efficiency; anomaly detection

PL

informatyka; model adaptacyjny; modelowanie obliczeniowe; zbiór przybliżony; odporność; wydajność obliczeniowa; wykrywanie anomalii

• Wydawca: Polskie Towarzystwo Informatyczne
• Czasopismo: Annals of Computer Science and Information Systems
• Rocznik: 2022
• Tom: Vol. 30
• Strony: 269--278
• Opis fizyczny: Bibliogr. 29 poz.,wz.

Twórcy

autor

Theerens Adnan

• Ghent University, Ghent, Belgium Computational Web Intelligence Dept. of Applied Mathematics, Computer Science and Statistics

autor

Cornelis Chris

• Ghent University, Ghent, Belgium Computational Web Intelligence Dept. of Applied Mathematics, Computer Science and Statistics

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Uwagi

1. The research reported in this paper was conducted with the financial support of the Odysseus programme of the Research Foundation – Flanders (FWO). The grant number is G0H9118N.

2. Track 5: 4th International Symposium on Rough Sets: Theory and Applications

3. Opracowanie rekordu ze środków MEiN, umowa nr SONP/SP/546092/2022 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2022-2023).