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Quantum Fuzzy Inference Engine for Particle Accelerator Control / Acampora, Giovanni (Naples U. ; INFN, Naples) ; Grossi, Michele (CERN) ; Schenk, Michael (CERN) ; Schiattarella, Roberto (Naples U. ; INFN, Naples)
Recently, quantum computing has been proven as an ideal theory for the design of fuzzy inference engines, thanks to its capability to efficiently solve the rule explosion problem. In this scenario, a quantum fuzzy inference engine (QFIE) was proposed as a quantum algorithm able to generate an exponential computational advantage over conventional fuzzy inference engines. [...]
2024 - 13 p. - Published in : IEEE Trans. Quantum Eng. 5 (2024) 1-13 Fulltext: PDF;

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A Comparison of Quantum Computer Architectures in Running Fuzzy Inference Engines / Acampora, Giovanni (Naples U.) ; Grossi, Michele (CERN) ; Schiattarella, Roberto (Naples U.)
The increasing need to work in environments characterized by a large number of variables and data is driving the development of ad hoc fuzzy reasoners. Recently, the first quantum fuzzy inference engine (QFIE) has been proposed to evaluate fuzzy rules in parallel on quantum computers, whose design hardware is based on different technologies such as superconductors, photonics, trap-ion, cold atoms, and so on. [...]
2023 - 6 p. - Published in : 10.1109/FUZZ52849.2023.10309673
In : 2023 IEEE International Conference on Fuzzy Systems (FUZZ 2023), Songdo Incheon, Korea, 13 - 17 Aug 2023

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