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Pourabdollah, A 
ORCID: https://orcid.org/0000-0001-7737-1393, Wilmott, C ORCID: https://orcid.org/0000-0003-4738-4227, Schiattarella, R and Acampora, G,
2023.
Fuzzy inference on quantum annealers.
In:
2023 IEEE International Conference on Fuzzy Systems (FUZZ).
IEEE.
ISBN 9798350332292
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Abstract
Quantum computers can potentially perform certain types of optimisation problems much more efficiently than classical computers, making them a promising tool for solving complex fuzzy logic problems. In two recent developments, based on solving Quadratic Unconstrained Binary Optimization (QUBO) problems on a type of quantum computers known as quantum annealers, we have introduced novel representations of a) fuzzy sets; b) implementations of some basic fuzzy logic operators (union, intersection, alpha-cut and maximum) and; c) the centroid defuzzification. In this paper, the previous works are further extended by presenting an implementation of Mamdani inference on the quantum annealer machines. We first present how the fuzzy rules can be formulated for such an implementation, then we present how to cascade different quantum-fuzzy operators in order to implement the quantum-fuzzy inference, and finally, a sample implementation of the inference on a real quantum computer is demonstrated. Having the main components of a rule-based fuzzy logic system implemented on quantum computers, this paper provides an integrated solution for implementing a whole fuzzy rule-based system on quantum computers.
| Item Type: | Chapter in book |
|---|---|
| Description: | Paper presented at 2023 IEEE International Conference on Fuzzy Systems (FUZZ), Incheon, Republic of Korea, 13-17 Aug 2023. |
| Creators: | Pourabdollah, A., Wilmott, C., Schiattarella, R. and Acampora, G. |
| Publisher: | IEEE |
| Date: | 9 November 2023 |
| ISBN: | 9798350332292 |
| Identifiers: | Number Type 10.1109/fuzz52849.2023.10309732 DOI 1835411 Other |
| Rights: | © 2023 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. |
| Divisions: | Schools > School of Science and Technology |
| Record created by: | Laura Ward |
| Date Added: | 16 Nov 2023 10:26 |
| Last Modified: | 16 Nov 2023 10:26 |
| URI: | https://irep.ntu.ac.uk/id/eprint/50391 |
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