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Comparing Performance Potentials of Classical and Intuitionistic Fuzzy Systems in Terms of Sculpting the State Space (2019)
Journal Article
Mendel, J. M., Eyoh, I., & John, R. (2020). Comparing Performance Potentials of Classical and Intuitionistic Fuzzy Systems in Terms of Sculpting the State Space. IEEE Transactions on Fuzzy Systems, 28(9), 2244-2254. https://doi.org/10.1109/TFUZZ.2019.2933786

This paper provides new application-independent perspectives about the performance potential of an intuitionistic (I-) fuzzy system over a (classical) TSK fuzzy system. It does this by extending sculpting the state space works from a TSK fuzzy system... Read More about Comparing Performance Potentials of Classical and Intuitionistic Fuzzy Systems in Terms of Sculpting the State Space.

The quantification of subjectivity: The R-fuzzy grey analysis framework (2019)
Journal Article
Khuman, A. S., Yang, Y., & John, R. (2019). The quantification of subjectivity: The R-fuzzy grey analysis framework. Expert Systems with Applications, 136, 201-216. https://doi.org/10.1016/j.eswa.2019.06.043

This paper puts forward a newly derived framework for capturing and inferring from subjective based uncertainty for any given observation. The framework is referred to as the R-fuzzy grey analysis framework (RfGAf), which itself is comprised of 3 dis... Read More about The quantification of subjectivity: The R-fuzzy grey analysis framework.

New Entropy-Based Similarity Measure between Interval-Valued Intuitionstic Fuzzy Sets (2019)
Journal Article
Mohamed, S. S., Abdalla, A., & John, R. I. (2019). New Entropy-Based Similarity Measure between Interval-Valued Intuitionstic Fuzzy Sets. Axioms, 8(2), 1-11. https://doi.org/10.3390/axioms8020073

In this paper we propose a new approach to construct similarity measures using the entropy measure for Interval-Valued Intuitionistic Fuzzy Sets. In addition, we provide several illustrative examples to demonstrate the practicality and effectivenes... Read More about New Entropy-Based Similarity Measure between Interval-Valued Intuitionstic Fuzzy Sets.

Overlapping Clusters and Support Vector Machines Based Interval Type-2 Fuzzy System for the Prediction of Peptide Binding Affinity (2019)
Journal Article
Uslan, V., Seker, H., & John, R. (2019). Overlapping Clusters and Support Vector Machines Based Interval Type-2 Fuzzy System for the Prediction of Peptide Binding Affinity. IEEE Access, 7, 49756-49764. https://doi.org/10.1109/access.2019.2910078

In the post-genome era, it is becoming more complex to process high dimensional, low-instance available, and nonlinear biological datasets. This paper aims to address these characteristics as they have adverse effects on the performance of predictive... Read More about Overlapping Clusters and Support Vector Machines Based Interval Type-2 Fuzzy System for the Prediction of Peptide Binding Affinity.