Medical diagnosis using interval type-2 fuzzy similarity measures
Author:
Funder
Deanship of Scientific Research, Princess Nourah Bint Abdulrahman University
Publisher
Springer Science and Business Media LLC
Link
https://link.springer.com/content/pdf/10.1007/s10586-024-04485-5.pdf
Reference49 articles.
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2. Ben Ayed, A., Ben Halima, M., Cherif, S., et al.: Robust clustering based possibilistic type-2 fuzzy c-means for noisy datasets. In: Enabling Machine Learning Applications in Data Science: Proceedings of Arab Conference for Emerging Technologies 2020, pp. 115–129. Springer (2021)
3. Bilgin, A., Hagras, H., Alghazzawi, D., et al.: Employing an enhanced interval approach to encode words into linear general type-2 fuzzy sets for computing with words applications. In: 2015 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE), pp. 1–8 (2015). https://doi.org/10.1109/FUZZ-IEEE.2015.7337848
4. Bustince, H.: Indicator of inclusion grade for interval-valued fuzzy sets. application to approximate reasoning based on interval-valued fuzzy sets. Int. J. Approx. Reason. 23(3), 137–209 (2000)
5. Chaabouni, T., Kchaou, H., Khemakhem, M.: Agent technology based resources management in cloud computing. In: 2013 World Congress on Computer and Information Technology (WCCIT), pp. 1–3 (2013). https://doi.org/10.1109/WCCIT.2013.6618659
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