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Comparing Intervals Using Type Reduction (2020)
Conference Proceeding
Runkler, T. A., Chen, C., Coupland, S., & John, R. (2020). Comparing Intervals Using Type Reduction. In 2020 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE) (1-6). https://doi.org/10.1109/fuzz48607.2020.9177675

Many decision making processes are based on choosing options with maximum utility. Often utility assessments are associated with uncertainty, which may be mathematically modeled by intervals of utilities. Intervals of utilities may be mapped to singl... Read More about Comparing Intervals Using Type Reduction.

FuzzyR: An Extended Fuzzy Logic Toolbox for the R Programming Language (2020)
Conference Proceeding
Chen, C., Razak, T. R., & Garibaldi, J. M. (2020). FuzzyR: An Extended Fuzzy Logic Toolbox for the R Programming Language. In 2020 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE) (1-8). https://doi.org/10.1109/fuzz48607.2020.9177780

This paper presents an R package FuzzyR which is an extended fuzzy logic toolbox for the R programming language. FuzzyR is a continuation of the previous Fuzzy R toolboxes such as FuzzyToolkitUoN. Whilst keeping existing functionalities of the previo... Read More about FuzzyR: An Extended Fuzzy Logic Toolbox for the R Programming Language.

Performance and Interpretability in Fuzzy Logic Systems – can we have both? (2020)
Conference Proceeding
Pekaslan, D., Chen, C., Wagner, C., & Garibaldi, J. M. (2020). Performance and Interpretability in Fuzzy Logic Systems – can we have both?.

Fuzzy Logic Systems can provide a good level of interpretability and may provide a key building block as part of a growing interest in explainable AI. In practice, the level of interpretability of a given fuzzy logic system is dependent on how well i... Read More about Performance and Interpretability in Fuzzy Logic Systems – can we have both?.

A Comprehensive Study of the Efficiency of Type-Reduction Algorithms (2020)
Journal Article
Chen, C., Wu, D., Garibaldi, J. M., John, R. I., Twycross, J., & Mendel, J. M. (2021). A Comprehensive Study of the Efficiency of Type-Reduction Algorithms. IEEE Transactions on Fuzzy Systems, 29(6), 1556 -1566. https://doi.org/10.1109/tfuzz.2020.2981002

Improving the efficiency of type-reduction algorithms continues to attract research interest. Recently, there have been some new type-reduction approaches claiming that they are more efficient than the well-known algorithms such as the enhanced Karni... Read More about A Comprehensive Study of the Efficiency of Type-Reduction Algorithms.