期刊
IEEE TRANSACTIONS ON FUZZY SYSTEMS
卷 30, 期 8, 页码 3389-3394出版社
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TFUZZ.2021.3113561
关键词
Quantum computing; Fuzzy sets; Qubit; Computers; Annealing; Computational modeling; Fuzzy logic; Fuzzy logic; quantum computing; simulated annealing
Quantum computation, utilizing quantum mechanics effects, is expected to have a significant impact on the field of computing and the application of fuzzy systems. This article introduces a novel representation of fuzzy sets and operators based on quadratic unconstrained binary optimization problems to implement fuzzy inference engines on quantum computers.
Quantum computation is going to revolutionize the world of computing by enabling the design of massive parallel algorithms that solve hard problems in an efficient way, thanks to the exploitation of quantum mechanics effects, such as superposition, entanglement, and interference. These computational improvements could strongly influence the way how fuzzy systems are designed and used in contexts, such as Big Data, where computational efficiency represents a nonnegligible constraint to be taken into account. In order to pave the way toward this innovative scenario, this article introduces a novel representation of fuzzy sets and operators based on quadratic unconstrained binary optimization problems, so as to enable the implementation of fuzzy inference engines on a type of quantum computers known as quantum annealers.
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