The Design and Implementation of a Constrained Interval Type-2 Fuzzy System for Credit Card Fraud Detection

Wang, Xinxin; Li, Ming; Chen, Chao; Garibaldi, Jonathan M.

Abstract

Fuzzy systems with type-1, interval type-2 and general type-2 fuzzy sets have been widely applied in various fields. Constrained Interval Type-2 (CIT2) fuzzy sets and systems are an approach designed to improve the interpretability of type-2 fuzzy inference systems (FISs) by preserving the semantic values throughout the modelling and decision process, including in the type-reduction and defuzzification stages. Whilst all the steps necessary for building CIT2 inference systems have been established, there is still a challenge for people to build data-driven models based on CIT2 sets and apply them in practice. This paper presents a step-by-step design of a CIT2 fuzzy inference system featuring a case study in credit card fraud detection, utilising the Juzzy Constrained toolkit. The framework contains three parts: creating CIT2 membership functions from data based on the K-means algorithm; deriving fuzzy rules by using a decision tree model; and implementing the CIT2 FIS with the Juzzy Constrained toolkit available online. This constitutes the first end-to-end demonstration of designing, creating and implementing a CIT2 FIS in a fresh application context. This will support other researchers to explore CIT2 fuzzy systems.

Citation

Wang, X., Li, M., Chen, C., & Garibaldi, J. M. (2023, August). The Design and Implementation of a Constrained Interval Type-2 Fuzzy System for Credit Card Fraud Detection. Presented at 2023 IEEE International Conference on Fuzzy Systems (FUZZ), Songdo Incheon, Korea

• Presentation Conference Type: Edited Proceedings
• Conference Name: 2023 IEEE International Conference on Fuzzy Systems (FUZZ)
• Start Date: Aug 13, 2023
• End Date: Aug 17, 2023
• Acceptance Date: Nov 9, 2023
• Online Publication Date: Nov 9, 2023
• Publication Date: Aug 13, 2023
• Deposit Date: Nov 5, 2024
• Publisher: Institute of Electrical and Electronics Engineers
• Peer Reviewed: Peer Reviewed
• Pages: 353-359
• Book Title: 2023 IEEE International Conference on Fuzzy Systems (FUZZ)
• ISBN: 979-8-3503-3229-2
• DOI: https://doi.org/10.1109/fuzz52849.2023.10309692
• Public URL: https://nottingham-repository.worktribe.com/output/27583547
• Publisher URL: https://ieeexplore.ieee.org/document/10309692