Uma Revisão da Literatura em Sistemas Quantum-Fuzzy
Resumo
Esta Revisão Sistemática da Literatura (RSL) busca estudos mais recentes, focados na integração de conceitos e técnicas da Lógica Fuzzy (LF) simulados via Computação Quântica (CQ), que atualmente também faz uso de extensões de técnicas da Inteligência Computacional (IC). Através da RSL foram selecionados 19 trabalhos no estado da arte, no período de 2023 a 2025, mostrando a integração dos conceitos da LF via sistemas quânticos na pesquisa por novas abordagens de simulações de Sistemas Flexíveis (SF). Essa RSL contribui para uma melhor compreensão da CQ reportando o incremento no interesse e na sinergia entre estas áreas.
Palavras-chave:
quantum fuzzy, revisão sistemática, computação quântica, lógica fuzzy
Referências
Acampora, G., Chiatto, A., and Vitiello, A. (2025a). Fuzzy clustering-based transferability of qaoa parameters for solving vertex cover problems. In 2025 IEEE Conference on Fuzzy Systems, pages 01–06. IEEE Xplore. DOI: 10.1109/FUZZ62266.2025.11152203
Acampora, G., Cuzzocrea, A., Lapegna, M., Schiattarella, R., and Vitiello, A. (2025b). Fuzzy reward-based reinforcement learning for clifford circuit synthesis. In 2025 IEEE Conference on Fuzzy Systems, pages 01–06. IEEE Xplore. DOI: 10.1109/FUZZ62266.2025.11152245
Acampora, G., Schiattarella, R., and Vitiello, A. (2023). On the implementation of fuzzy inference engines on quantum computers. IEEE Transactions on Fuzzy Systems, 31(5):1419–1433. DOI: 10.1109/TFUZZ.2022.3202348
Acampora, G., Schiattarella, R., and Vitiello, A. (2025c). Hybrid quantum-classical interval type-2 mamdani fuzzy systems. In 2025 IEEE Conference on Fuzzy Systems, pages 01–06. IEEE Xplore. DOI: 10.1109/FUZZ62266.2025.11152074
Anjaria, K. (2024). Quantum model regression for generating fuzzy numbers in adiabatic quantum computing. Information Sciences, 678:121018. DOI: 10.1016/j.ins.2024.121018
Botelho, C., Buss, J., Santos, H., Lucca, G., Cruz, A., Yamin, A., and Reiser, R. (2024a). Exploring social decision models through quantum fuzzy approaches. In 2024 IEEE International Conference on Systems, Man, and Cybernetics (SMC), pages 3025–3030. IEEE. DOI: 10.1109/SMC54092.2024.10831576
Botelho, C., LArissa Schonhofen, L., Santos, H., Lucca, G., Cruz, A., Yamin, A., and Reiser, R. (2025a). Quantum-fuzzy integration for emotion-aware in computational intelligent systems. In 2025 IEEE Conference on Fuzzy Systems, pages 01–06. IEEE Xplore. DOI: 10.1109/FUZZ62266.2025.11152099
Botelho, C., Santos, H., Lucca, G., Cruz, A., Yamin, A. C., and Reiser, R. H. S. (2024b). A novel quantum fuzzy approach to interpret dilemmas of game theory. In 2024 L Latin American Computer Conference (CLEI), pages 1–9. IEEE. DOI: 10.1109/CLEI64178.2024.10700212
Botelho, C., Schonhofen, L., Santos, H., Lucca, G., Yamin, A. C., and Reiser, R. H. S. (2025b). Toward a quantum fuzzy approach for emotion modeling in parent-child interactivity. In Proceedings of the 17th Intl Conf on Agents and Art Intelligence (ICAART 2025) - Volume 3, pages 1297–1303. SCITEPRESS – Science and Technology Publications, Lda. DOI: 10.5220/0013323700003890
Buss, J., Novack, B., Botelho, C., Santos, H., Lucca, G., Cruz, A., Yamin, A., and Reiser, R. (2024). Fusion data on fuzzy modality: From algebraic interpretations to quantum simulations via qiskit platform. In 2024 IEEE International Conference on Systems, Man, and Cybernetics (SMC), pages 3602–3607. IEEE. DOI: 10.1109/SMC54092.2024.10832070
Buss, J., Novak, B., Santos, H., Lucca, G., Oliveira, L., Yamin, A., Cruz, A., and Reiser, R. (2025). IBM-Qiskit simulations for quantum-fuzzy interpretations of X(N)or-connectives using overlapping and grouping aggregations. In 2025 IEEE Conference on Fuzzy Systems, pages 01–06. IEEE Xplore. DOI: 10.1109/FUZZ62266.2025.11152232
Chen, T., Bin Zhang, S., Wang, Q., and Chang, Y. (2023). Quantum fuzzy regression model for uncertain environment. Computers, Materials & Continua, 75(2). DOI: 10.32604/cmc.2023.033284
de Avila, A. B., Reiser, R., Pilla, M. L., and Yamin, A. C. Interpreting xor intuitionistic fuzzy connectives from quantum fuzzy computing. In Guervós, J. J. M., Garibaldi, J. M., Linares-Barranco, A., Madani, K., and Warwick, K., editors, Proceedings of the 11th Intl Joint Conf on Comp Intelligence, IJCCI 2019, Vienna, Austria, pages = 288–295, doi = 10.5220/0008169702880295,. DOI: 10.5220/0008169702880295
Dong, Y., Zhu, T., Li, X., Dezert, J., Zhou, R., Zhu, C., Cao, L., and Ge, S. S. (2025). Quantum conflict measurement in decision making for out-of-distribution detection. arXiv preprint arXiv:2505.06516. DOI: 10.48550/arXiv.2505.06516
Hou, M., Zhang, S., and Xia, J. (2022). Quantum fuzzy k-means algorithm based on fuzzy theory. In Sun, X., Zhang, X., Xia, Z., and Bertino, E., editors, Artificial Intelligence and Security - 8th International Conference, ICAIS 2022, Qinghai, China, July 15-20, 2022, Proceedings, Part I, volume 13338 of Lecture Notes in Computer Science, pages 348–356. Springer. DOI: 10.1007/978-3-031-06794-5_28
Huang, C. and Zhang, S. (2024). Adversarial examples detection based on quantum fuzzy convolution neural network. Quantum Information Processing, 23(4):143. DOI: 10.1007/s11128-024-04310-3
Huang, C., Zhang, S., Chang, Y., and Yan, L. (2024). Quantum metric learning with fuzzy-informed learning. Physica A: Statistical Mechanics and its Applications, 643:129801. DOI: 10.1016/j.physa.2024.129801
Khalil, H., Elshazly, O., Baihan, A., El-Shafai, W., and Shaheen, O. (2024). Quantum neural networks based Lyapunov stability and adaptive learning rates for identification of nonlinear systems. Ain Shams Engineering Journal, 15(8):102851. DOI: 10.1016/j.asej.2024.102851
Khushal, R. and Fatima, U. (2025). Fuzzy quantum machine learning (fqml) logic for optimized disease prediction. Computers in Biology and Medicine, 192:110315. DOI: 10.1016/j.compbiomed.2025.110315
Lee, C.-S., Wang, M.-H., Chen, C.-Y., Yang, S.-C., Reformat, M., Kubota, N., and Pourabdollah, A. (2025). Quantum fuzzy inference engine with generative ai and taide kg for taiwanese/english co-learning. In 2025 IEEE Conference on Fuzzy Systems, pages 01–06. IEEE Xplore.
Lu, Y., Sigov, A., Ratkin, L., Ivanov, L. A., and Zuo, M. (2023). Quantum computing and industrial information integration: A review. Journal of Industrial Information Integration, page 100511. DOI: 10.1016/j.jii.2023.100511
Pollock, A. and Berge, E. (2018). How to do a systematic review. International Journal of Stroke, 13(2):138–156. DOI: 10.1177/1747493017743796
Pourabdollah, A., Acampora, G., and Schiattarella, R. (2022). Fuzzy logic on quantum annealers. IEEE Transactions on Fuzzy Systems, 30(8):3389–3394. DOI: 10.1109/TFUZZ.2021.3113561
Sachan, A. and Kumar, N. (2023). Sdn control-enabled and time-quantum-driven max-pressure approach for intersection management in smart city. IEEE Systems Journal, 17(1):1694–1702. DOI: 10.1109/JSYST.2022.3211933
Sigov, A., Ratkin, L., and Ivanov, L. A. (2022). Quantum information technology. Journal of Industrial Information Integration, 28:100365. DOI: 10.1016/j.jii.2022.100365
Yan, J.-T. (2023). Fuzzy-based balanced partitioning under capacity and size-tolerance constraints in distributed quantum circuits. IEEE Transactions on Quantum Engineering, 4:5100115. DOI: 10.1109/TQE.2023.3272023
Zadeh, L. A. (1978). Fuzzy sets as a basis for a theory of possibility. Fuzzy Sets and Systems, 1(1):3–28. DOI: 10.1016/0165-0114(78)90029-5
Zhang, K. and Zhang, J. (2022). A technique for designing nano-scale circuits using a fuzzy logic and nature-inspired fish swarm optimization algorithm. Optik, 268:169756. DOI: 10.1016/j.ijleo.2022.169756
Acampora, G., Cuzzocrea, A., Lapegna, M., Schiattarella, R., and Vitiello, A. (2025b). Fuzzy reward-based reinforcement learning for clifford circuit synthesis. In 2025 IEEE Conference on Fuzzy Systems, pages 01–06. IEEE Xplore. DOI: 10.1109/FUZZ62266.2025.11152245
Acampora, G., Schiattarella, R., and Vitiello, A. (2023). On the implementation of fuzzy inference engines on quantum computers. IEEE Transactions on Fuzzy Systems, 31(5):1419–1433. DOI: 10.1109/TFUZZ.2022.3202348
Acampora, G., Schiattarella, R., and Vitiello, A. (2025c). Hybrid quantum-classical interval type-2 mamdani fuzzy systems. In 2025 IEEE Conference on Fuzzy Systems, pages 01–06. IEEE Xplore. DOI: 10.1109/FUZZ62266.2025.11152074
Anjaria, K. (2024). Quantum model regression for generating fuzzy numbers in adiabatic quantum computing. Information Sciences, 678:121018. DOI: 10.1016/j.ins.2024.121018
Botelho, C., Buss, J., Santos, H., Lucca, G., Cruz, A., Yamin, A., and Reiser, R. (2024a). Exploring social decision models through quantum fuzzy approaches. In 2024 IEEE International Conference on Systems, Man, and Cybernetics (SMC), pages 3025–3030. IEEE. DOI: 10.1109/SMC54092.2024.10831576
Botelho, C., LArissa Schonhofen, L., Santos, H., Lucca, G., Cruz, A., Yamin, A., and Reiser, R. (2025a). Quantum-fuzzy integration for emotion-aware in computational intelligent systems. In 2025 IEEE Conference on Fuzzy Systems, pages 01–06. IEEE Xplore. DOI: 10.1109/FUZZ62266.2025.11152099
Botelho, C., Santos, H., Lucca, G., Cruz, A., Yamin, A. C., and Reiser, R. H. S. (2024b). A novel quantum fuzzy approach to interpret dilemmas of game theory. In 2024 L Latin American Computer Conference (CLEI), pages 1–9. IEEE. DOI: 10.1109/CLEI64178.2024.10700212
Botelho, C., Schonhofen, L., Santos, H., Lucca, G., Yamin, A. C., and Reiser, R. H. S. (2025b). Toward a quantum fuzzy approach for emotion modeling in parent-child interactivity. In Proceedings of the 17th Intl Conf on Agents and Art Intelligence (ICAART 2025) - Volume 3, pages 1297–1303. SCITEPRESS – Science and Technology Publications, Lda. DOI: 10.5220/0013323700003890
Buss, J., Novack, B., Botelho, C., Santos, H., Lucca, G., Cruz, A., Yamin, A., and Reiser, R. (2024). Fusion data on fuzzy modality: From algebraic interpretations to quantum simulations via qiskit platform. In 2024 IEEE International Conference on Systems, Man, and Cybernetics (SMC), pages 3602–3607. IEEE. DOI: 10.1109/SMC54092.2024.10832070
Buss, J., Novak, B., Santos, H., Lucca, G., Oliveira, L., Yamin, A., Cruz, A., and Reiser, R. (2025). IBM-Qiskit simulations for quantum-fuzzy interpretations of X(N)or-connectives using overlapping and grouping aggregations. In 2025 IEEE Conference on Fuzzy Systems, pages 01–06. IEEE Xplore. DOI: 10.1109/FUZZ62266.2025.11152232
Chen, T., Bin Zhang, S., Wang, Q., and Chang, Y. (2023). Quantum fuzzy regression model for uncertain environment. Computers, Materials & Continua, 75(2). DOI: 10.32604/cmc.2023.033284
de Avila, A. B., Reiser, R., Pilla, M. L., and Yamin, A. C. Interpreting xor intuitionistic fuzzy connectives from quantum fuzzy computing. In Guervós, J. J. M., Garibaldi, J. M., Linares-Barranco, A., Madani, K., and Warwick, K., editors, Proceedings of the 11th Intl Joint Conf on Comp Intelligence, IJCCI 2019, Vienna, Austria, pages = 288–295, doi = 10.5220/0008169702880295,. DOI: 10.5220/0008169702880295
Dong, Y., Zhu, T., Li, X., Dezert, J., Zhou, R., Zhu, C., Cao, L., and Ge, S. S. (2025). Quantum conflict measurement in decision making for out-of-distribution detection. arXiv preprint arXiv:2505.06516. DOI: 10.48550/arXiv.2505.06516
Hou, M., Zhang, S., and Xia, J. (2022). Quantum fuzzy k-means algorithm based on fuzzy theory. In Sun, X., Zhang, X., Xia, Z., and Bertino, E., editors, Artificial Intelligence and Security - 8th International Conference, ICAIS 2022, Qinghai, China, July 15-20, 2022, Proceedings, Part I, volume 13338 of Lecture Notes in Computer Science, pages 348–356. Springer. DOI: 10.1007/978-3-031-06794-5_28
Huang, C. and Zhang, S. (2024). Adversarial examples detection based on quantum fuzzy convolution neural network. Quantum Information Processing, 23(4):143. DOI: 10.1007/s11128-024-04310-3
Huang, C., Zhang, S., Chang, Y., and Yan, L. (2024). Quantum metric learning with fuzzy-informed learning. Physica A: Statistical Mechanics and its Applications, 643:129801. DOI: 10.1016/j.physa.2024.129801
Khalil, H., Elshazly, O., Baihan, A., El-Shafai, W., and Shaheen, O. (2024). Quantum neural networks based Lyapunov stability and adaptive learning rates for identification of nonlinear systems. Ain Shams Engineering Journal, 15(8):102851. DOI: 10.1016/j.asej.2024.102851
Khushal, R. and Fatima, U. (2025). Fuzzy quantum machine learning (fqml) logic for optimized disease prediction. Computers in Biology and Medicine, 192:110315. DOI: 10.1016/j.compbiomed.2025.110315
Lee, C.-S., Wang, M.-H., Chen, C.-Y., Yang, S.-C., Reformat, M., Kubota, N., and Pourabdollah, A. (2025). Quantum fuzzy inference engine with generative ai and taide kg for taiwanese/english co-learning. In 2025 IEEE Conference on Fuzzy Systems, pages 01–06. IEEE Xplore.
Lu, Y., Sigov, A., Ratkin, L., Ivanov, L. A., and Zuo, M. (2023). Quantum computing and industrial information integration: A review. Journal of Industrial Information Integration, page 100511. DOI: 10.1016/j.jii.2023.100511
Pollock, A. and Berge, E. (2018). How to do a systematic review. International Journal of Stroke, 13(2):138–156. DOI: 10.1177/1747493017743796
Pourabdollah, A., Acampora, G., and Schiattarella, R. (2022). Fuzzy logic on quantum annealers. IEEE Transactions on Fuzzy Systems, 30(8):3389–3394. DOI: 10.1109/TFUZZ.2021.3113561
Sachan, A. and Kumar, N. (2023). Sdn control-enabled and time-quantum-driven max-pressure approach for intersection management in smart city. IEEE Systems Journal, 17(1):1694–1702. DOI: 10.1109/JSYST.2022.3211933
Sigov, A., Ratkin, L., and Ivanov, L. A. (2022). Quantum information technology. Journal of Industrial Information Integration, 28:100365. DOI: 10.1016/j.jii.2022.100365
Yan, J.-T. (2023). Fuzzy-based balanced partitioning under capacity and size-tolerance constraints in distributed quantum circuits. IEEE Transactions on Quantum Engineering, 4:5100115. DOI: 10.1109/TQE.2023.3272023
Zadeh, L. A. (1978). Fuzzy sets as a basis for a theory of possibility. Fuzzy Sets and Systems, 1(1):3–28. DOI: 10.1016/0165-0114(78)90029-5
Zhang, K. and Zhang, J. (2022). A technique for designing nano-scale circuits using a fuzzy logic and nature-inspired fish swarm optimization algorithm. Optik, 268:169756. DOI: 10.1016/j.ijleo.2022.169756
Publicado
10/09/2025
Como Citar
SILVA, Gabriel; BRUM, Luis Henrique; REISER, Renata; YAMIN, Adenauer; CRUZ, Anderson; SANTOS, Helida; LUCCA, Giancarlo; OLIVEIRA, Lizandro.
Uma Revisão da Literatura em Sistemas Quantum-Fuzzy. In: WORKSHOP-ESCOLA DE INFORMÁTICA TEÓRICA (WEIT), 8. , 2025, Ponta Grossa/PR.
Anais [...].
Porto Alegre: Sociedade Brasileira de Computação,
2025
.
p. 92-101.
