A Hybrid Model Combining Bipolar Fuzzy Sets and Rough Sets in Semirings with Applications in Anomaly Detection
DOI:
https://doi.org/10.65419/albahit.v5i2.143Keywords:
Bipolar fuzzy set, Rough set, Hybrid model, Semiring, Anomaly detectionAbstract
This research presents a hybrid mathematical model that combines two modern theories for handling uncertainty: Bipolar Fuzzy Sets and Rough Sets, within the algebraic framework of Semirings. The proposed model is capable of representing both positive and negative information simultaneously while also handling imprecision caused by incomplete information. The model is applied to anomaly detection in databases. Experimental results on a standard dataset show that the proposed hybrid model outperforms traditional methods in detection accuracy.
References
[1] -Zhang, W. R. (1998). "Bipolar fuzzy sets and relations." Proceedings of IEEE Conference on Fuzzy Systems, 305-309.
[2]- Pawlak, Z. (1982). "Rough sets." International Journal of Computer & Information Sciences, 11(5), 341-356.
[3]- Dubois, D., & Prade, H. (1990). "Rough fuzzy sets and fuzzy rough sets." International Journal of General Systems, 17(2-3), 191-209.
[4] -Shabir, M., et al. (2025). "Roughness of (α,β)-bipolar fuzzy ideals in semigroups." Computational and Applied Mathematics, 44(1), 24.
[5]- Gulistan, M., et al. (2025). "Dombi aggregation operator in terms of complex bipolar fuzzy sets." Complex & Intelligent Systems, 11, Article 483.
Ambark Ashat. (2025). Using the fuzzy center method to solve linear fractional fuzzy differential equations of order n with initial conditions. Journal of Libyan Academy Bani Walid, 1(4), 253–270. https://doi.org/10.61952/jlabw.v1i4.347


