Outputs (81)

A comparison between two types of Fuzzy TOPSIS method (2015)
Presentation / Conference Contribution
Madi, E., Garibaldi, J. M., & Wagner, C. A comparison between two types of Fuzzy TOPSIS method. Presented at 2015 IEEE International Conference on Systems, Man, and Cybernetics (SMC)

Multi Criteria Decision Making methods have been developed to solve complex real-world decision problems. The Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) is currently one of the most popular methods and has been shown to p... Read More about A comparison between two types of Fuzzy TOPSIS method.

Data-informed fuzzy measures for fuzzy integration of intervals and fuzzy numbers (2014)
Journal Article
Havens, T. C., Anderson, D. T., & Wagner, C. (2015). Data-informed fuzzy measures for fuzzy integration of intervals and fuzzy numbers. IEEE Transactions on Fuzzy Systems, 23(5), https://doi.org/10.1109/TFUZZ.2014.2382133

The fuzzy integral (FI) with respect to a fuzzy measure (FM) is a powerful means of aggregating information. The most popular FIs are the Choquet and Sugeno, and most research focuses on these two variants. The arena of the FM is much more populated,... Read More about Data-informed fuzzy measures for fuzzy integration of intervals and fuzzy numbers.

Analysing fuzzy sets through combining measures of similarity and distance (2014)
Presentation / Conference Contribution
McCulloch, J., Wagner, C., & Aickelin, U. Analysing fuzzy sets through combining measures of similarity and distance. Presented at 2014 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE)

Reasoning with fuzzy sets can be achieved through measures such as similarity and distance. However, these measures can often give misleading results when considered independently, for example giving the same value for two different pairs of fuzzy se... Read More about Analysing fuzzy sets through combining measures of similarity and distance.

Comparison of distance metrics for hierarchical data in medical databases (2014)
Presentation / Conference Contribution
Hassan, D., Aickelin, U., & Wagner, C. (2014, July). Comparison of distance metrics for hierarchical data in medical databases. Presented at 2014 International Joint Conference on Neural Networks (IJCNN)

Distance metrics are broadly used in different research areas and applications, such as bio-informatics, data mining and many other fields. However, there are some metrics, like pg-gram and Edit Distance used specifically for data with a hierarchical... Read More about Comparison of distance metrics for hierarchical data in medical databases.

A fuzzy directional distance measure (2014)
Presentation / Conference Contribution
McCulloch, J., Hinde, C., Wagner, C., & Aickelin, U. A fuzzy directional distance measure. Presented at 2014 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE)

The measure of distance between two fuzzy sets is a fundamental tool within fuzzy set theory, however, distance measures currently within the literature use a crisp value to represent the distance between fuzzy sets. A real valued distance measure is... Read More about A fuzzy directional distance measure.

From Interval-Valued Data to General Type-2 Fuzzy Sets (2014)
Journal Article
Wagner, C., Miller, S., Garibaldi, J. M., Anderson, D. T., & Havens, T. C. (2015). From Interval-Valued Data to General Type-2 Fuzzy Sets. IEEE Transactions on Fuzzy Systems, 23(2), 248-269. https://doi.org/10.1109/tfuzz.2014.2310734

In this paper, a new approach is presented to model interval-based data using fuzzy sets (FSs). Specifically, we show how both crisp and uncertain intervals (where there is uncertainty about the endpoints of intervals) collected from individual or mu... Read More about From Interval-Valued Data to General Type-2 Fuzzy Sets.

Extension of the Fuzzy Integral for General Fuzzy Set-Valued Information (2014)
Journal Article
Anderson, D. T., Havens, T. C., Wagner, C., Keller, J. M., Anderson, M. F., & Wescott, D. J. (2014). Extension of the Fuzzy Integral for General Fuzzy Set-Valued Information. IEEE Transactions on Fuzzy Systems, 22(6), 1625-1639. https://doi.org/10.1109/TFUZZ.2014.2302479

The fuzzy integral (FI) is an extremely flexible aggregation operator. It is used in numerous applications, such as image processing, multicriteria decision making, skeletal age-at-death estimation, and multisource (e.g., feature, algorithm, sensor,... Read More about Extension of the Fuzzy Integral for General Fuzzy Set-Valued Information.

Measuring the directional distance between fuzzy sets (2013)
Presentation / Conference Contribution
McCulloch, J., Wagner, C., & Aickelin, U. Measuring the directional distance between fuzzy sets. Presented at UKCI 2013, the 13th Annual Workshop on Computational Intelligence

The measure of distance between two fuzzy sets is a fundamental tool within fuzzy set theory. However, current distance measures within the literature do not account for the direction of change between fuzzy sets; a useful concept in a variety of app... Read More about Measuring the directional distance between fuzzy sets.

Creating personalised energy plans: from groups to individuals using Fuzzy C Means Clustering
Presentation / Conference Contribution
Dent, I., Wagner, C., Aickelin, U., & Rodden, T. Creating personalised energy plans: from groups to individuals using Fuzzy C Means Clustering. Presented at Digital Engagement 11

Changes in the UK electricity market mean that domestic
users will be required to modify their usage behaviour in
accordance with energy eciency targets. Clustering allows
usage data, collected at the household level, to be clustered
into groups... Read More about Creating personalised energy plans: from groups to individuals using Fuzzy C Means Clustering.

Extending similarity measures of interval type-2 fuzzy sets to general type-2 fuzzy sets
Presentation / Conference Contribution
McCulloch, J., Wagner, C., & Aickelin, U. Extending similarity measures of interval type-2 fuzzy sets to general type-2 fuzzy sets. Presented at IEEE International Conference on Fuzzy Systems 2013 (Fuzz-IEEE 2013)

Similarity measures provide one of the core tools
that enable reasoning about fuzzy sets. While many types of
similarity measures exist for type-1 and interval type-2 fuzzy sets, there are very few similarity measures that enable the comparison of... Read More about Extending similarity measures of interval type-2 fuzzy sets to general type-2 fuzzy sets.