Exploring the Intersection of Fuzzy Logic and Machine Learning: Applications and Advancements
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Publisher
Springer Nature Switzerland
Link
https://link.springer.com/content/pdf/10.1007/978-3-031-67192-0_6
Reference18 articles.
1. Chandre, P.R., Shendkar, B.D., Deshmukh, S., Kakade, S., Potdukhe, S.: Machine learning-enhanced advancements in quantum cryptography: a comprehensive review and future prospects. Int. J. Recent Innov. Trends Comput. Commun. 11(11s), 642–655 (2023). https://doi.org/10.17762/ijritcc.v11i11s.8300
2. Tekin, A.T., Cebi, F., Kaya, T.: Retention prediction in the gaming industry: fuzzy machine learning approach. In: Calisir, F. (ed.) Industrial Engineering in the Age of Business Intelligence: Selected Papers from the Virtual Global Joint Conference on Industrial Engineering and Its Application Areas, GJCIE 2021, October 30–31, 2021, pp. 103–117. Springer International Publishing, Cham (2023). https://doi.org/10.1007/978-3-031-08782-0_9
3. Ramiz, A., Vuqar, S.: Assessment of the effectiveness of marketing activities of commercial enterprises using the theory of fuzzy sets. In: Cengiz Kahraman, A., Tolga, C., Onar, S.C., Cebi, S., Oztaysi, B., Sari, I.U. (eds.) Intelligent and Fuzzy Systems: Digital Acceleration and The New Normal - Proceedings of the INFUS 2022 Conference, Volume 1, pp. 135–141. Springer International Publishing, Cham (2022). https://doi.org/10.1007/978-3-031-09173-5_18
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