All Outputs (9)

A Restricted Parametrized Model for Interval-Valued Regression (2023)
Conference Proceeding
Ying, J., Kabir, S., & Wagner, C. (2023). A Restricted Parametrized Model for Interval-Valued Regression. . https://doi.org/10.1109/fuzz52849.2023.10309686

This paper explores the parameter generation of the existing ‘Parametrized Model’ (PM) as the state-of-the-art linear interval-valued regression model, highlighting that its strong performance may arise from unexpected behavior. Focusing on the appro... Read More about A Restricted Parametrized Model for Interval-Valued Regression.

Visualization of Interval Regression for Facilitating Data and Model Insight (2022)
Conference Proceeding
Kabir, S., & Wagner, C. (2022). Visualization of Interval Regression for Facilitating Data and Model Insight. . https://doi.org/10.1109/fuzz-ieee55066.2022.9882717

With growing significance of interval-valued data, interest in artificial intelligence methods tailored to this data type is similarly increasing across a range of application domains. Here, regression, i.e., the modelling of the association between... Read More about Visualization of Interval Regression for Facilitating Data and Model Insight.

Interval-Valued Regression - Sensitivity to Data Set Features (2021)
Conference Proceeding
Kabir, S., & Wagner, C. (in press). Interval-Valued Regression - Sensitivity to Data Set Features. In 2021 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE). https://doi.org/10.1109/fuzz45933.2021.9494554

Regression represents one of the most basic building blocks of data analysis and AI. Despite growing interest in interval-valued data across various fields, approaches to establish regression models for interval-valued data which address and handle t... Read More about Interval-Valued Regression - Sensitivity to Data Set Features.

A Fuzzy Logic-Based Trust Estimation in Edge-Enabled Vehicular Ad Hoc Networks (2021)
Conference Proceeding
Hasan, M. M., Jahan, M., Kabir, S., & Wagner, C. (in press). A Fuzzy Logic-Based Trust Estimation in Edge-Enabled Vehicular Ad Hoc Networks. . https://doi.org/10.1109/fuzz45933.2021.9494428

Trust estimation of vehicles is vital for the correct functioning of Vehicular Ad Hoc Networks (VANETs) as it enhances their security by identifying reliable vehicles. However, accurate trust estimation still remains distant as existing works do not... Read More about A Fuzzy Logic-Based Trust Estimation in Edge-Enabled Vehicular Ad Hoc Networks.

A Bidirectional Subsethood Based Fuzzy Measure for Aggregation of Interval-Valued Data (2020)
Conference Proceeding
Kabir, S., & Wagner, C. (2020). A Bidirectional Subsethood Based Fuzzy Measure for Aggregation of Interval-Valued Data. In Information Processing and Management of Uncertainty in Knowledge-Based Systems (603-617). https://doi.org/10.1007/978-3-030-50143-3_48

Recent advances in the literature have leveraged the fuzzy integral (FI), a powerful multi-source aggregation operator, where a fuzzy measure (FM) is used to capture the worth of all combinations of subsets of sources. While in most applications, the... Read More about A Bidirectional Subsethood Based Fuzzy Measure for Aggregation of Interval-Valued Data.

Measuring Similarity Between Discontinuous Intervals - Challenges and Solutions (2019)
Conference Proceeding
Kabir, S., Wagner, C., Havens, T. C., & Anderson, D. T. (in press). Measuring Similarity Between Discontinuous Intervals - Challenges and Solutions. . https://doi.org/10.1109/fuzz-ieee.2019.8858862

Discontinuous intervals (DIs) arise in a wide range of contexts, from real world data capture of human opinion to α-cuts of non-convex fuzzy sets. Commonly, for assessing the similarity of DIs, the latter are converted into their continuous form, fol... Read More about Measuring Similarity Between Discontinuous Intervals - Challenges and Solutions.

A Bidirectional Subsethood Based Similarity Measure for Fuzzy Sets (2018)
Conference Proceeding
Kabir, S., Wagner, C., Havens, T. C., & Anderson, D. T. A Bidirectional Subsethood Based Similarity Measure for Fuzzy Sets. In 2018 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE). https://doi.org/10.1109/fuzz-ieee.2018.8491669

Similarity measures are useful for reasoning about fuzzy sets. Hence, many classical set-theoretic similarity measures have been extended for comparing fuzzy sets. In previous work, a set-theoretic similarity measure considering the bidirectional sub... Read More about A Bidirectional Subsethood Based Similarity Measure for Fuzzy Sets.

Determining Firing Strengths Through a Novel Similarity Measure to Enhance Uncertainty Handling in Non-singleton Fuzzy Logic Systems (2017)
Conference Proceeding
Pekaslan, D., Kabir, S., Garibaldi, J. M., & Wagner, C. (2017). Determining Firing Strengths Through a Novel Similarity Measure to Enhance Uncertainty Handling in Non-singleton Fuzzy Logic Systems. In Proceedings of the 9th International Joint Conference on Computational Intelligence - Volume 0IJCCI (83-90). https://doi.org/10.5220/0006502000830090

Non-singleton Fuzzy Logic Systems have the potential to tackle uncertainty within the design of fuzzy systems. The inference process has a major role in determining results, being partly based on the interaction of input and antecedent fuzzy sets (in... Read More about Determining Firing Strengths Through a Novel Similarity Measure to Enhance Uncertainty Handling in Non-singleton Fuzzy Logic Systems.

Novel similarity measure for interval-valued data based on overlapping ratio (2017)
Conference Proceeding
Kabir, S., Wagner, C., Havens, T. C., Anderson, D. T., & Aickelin, U. (2017). Novel similarity measure for interval-valued data based on overlapping ratio. . https://doi.org/10.1109/fuzz-ieee.2017.8015623

In computing the similarity of intervals, current similarity measures such as the commonly used Jaccard and Dice measures are at times not sensitive to changes in the width of intervals, producing equal similarities for substantially different pairs... Read More about Novel similarity measure for interval-valued data based on overlapping ratio.