Outputs (60)

Interval Agreement Weighted Average - Sensitivity to Data Set Features
Presentation / Conference Contribution
Zhao, Y., Wagner, C., Ryan, B., Pekaslan, D., & Navarro, J. (2024, June). Interval Agreement Weighted Average - Sensitivity to Data Set Features. Presented at 2024 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE), Yokohama, Japan

The growing use of intervals in fields like survey analysis necessitates effective aggregation methods that can summarize and represent such uncertain data representations. The Interval Agreement Approach (IAA) addresses this by aggregating interval... Read More about Interval Agreement Weighted Average - Sensitivity to Data Set Features.

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.

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.

Improving security requirements adequacy: an interval type 2 fuzzy logic security assessment system
Presentation / Conference Contribution
Hibshi, H., Breaux, T. D., & Wagner, C. (in press). Improving security requirements adequacy: an interval type 2 fuzzy logic security assessment system.

Organizations rely on security experts to improve the security of their systems. These professionals use background knowledge and experience to align known threats and vulnerabilities before selecting mitigation options. The substantial depth of expe... Read More about Improving security requirements adequacy: an interval type 2 fuzzy logic security assessment system.

Determining firing strengths through a novel similarity measure to enhance uncertainty handling in non-singleton fuzzy logic systems
Presentation / Conference Contribution
Pekaslan, D., Kabir, S., Wagner, C., & Garibaldi, J. M. (2017, November). Determining firing strengths through a novel similarity measure to enhance uncertainty handling in non-singleton fuzzy logic systems. Presented at International Joint Conference on Computational Intelligence (IJCCI 2017), Funchal, Madeira, Portugal

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.

Measuring the similarity between zSlices general type-2 fuzzy sets with non-normal Secondary membership functions
Presentation / Conference Contribution
McCulloch, J., & Wagner, C. (2016, June). Measuring the similarity between zSlices general type-2 fuzzy sets with non-normal Secondary membership functions. Presented at 2016 IEEE International Conference on Fuzzy Systems, FUZZ-IEEE 2016, Vancouver, BC, Canada

This paper presents a method of measuring the similarity between general type-2 fuzzy sets that may have non-normal secondary membership functions. Such fuzzy sets are increasingly common in applications such as the modelling of the subjective meanin... Read More about Measuring the similarity between zSlices general type-2 fuzzy sets with non-normal Secondary membership functions.

A similarity-based inference engine for non-singleton fuzzy logic systems
Presentation / Conference Contribution
Wagner, C., Pourabdollah, A., McCulloch, J., John, R., & Garibaldi, J. M. (2016, July). A similarity-based inference engine for non-singleton fuzzy logic systems. Presented at 2016 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE 2016), Vancouver, BC, Canada

In non-singleton fuzzy logic systems (NSFLSs) input uncertainties are modelled with input fuzzy sets in order to capture input uncertainty such as sensor noise. The performance of NSFLSs in handling such uncertainties depends both on the actual input... Read More about A similarity-based inference engine for non-singleton fuzzy logic systems.

Measuring agreement on linguistic expressions in medical treatment scenarios
Presentation / Conference Contribution
Navarro, J., Wagner, C., Aickelin, U., Green, L., & Ashford, R. (2016, December). Measuring agreement on linguistic expressions in medical treatment scenarios. Presented at 2016 IEEE Symposium Series on Computational Intelligence (SSCI), Athens, Greece

Quality of life assessment represents a key process of deciding treatment success and viability. As such, patients’ perceptions of their functional status and well-being are important inputs for impairment assessment. Given that patient completed que... Read More about Measuring agreement on linguistic expressions in medical treatment scenarios.

Efficient modeling and representation of agreement in interval-valued data
Presentation / Conference Contribution
Havens, T. C., Wagner, C., & Anderson, D. T. (2017, July). Efficient modeling and representation of agreement in interval-valued data. Presented at 2017 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE 2017), Naples, Italy

Recently, there has been much research into effective representation and analysis of uncertainty in human responses, with applications in cyber-security, forest and wildlife management, and product development, to name a few. Most of this research ha... Read More about Efficient modeling and representation of agreement in interval-valued data.

Exploring the use of type-2 fuzzy sets in multi-criteria decision making based on TOPSIS
Presentation / Conference Contribution
Madi, E., Garibaldi, J. M., & Wagner, C. (2017, July). Exploring the use of type-2 fuzzy sets in multi-criteria decision making based on TOPSIS. Presented at 2017 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE 2017), Naples, Italy

Multi-criteria decision making (MCDM) problems are a well known category of decision making problem that has received much attention in the literature, with a key approach being the Technique for Order Preference by Similarity to Ideal Solution (TOPS... Read More about Exploring the use of type-2 fuzzy sets in multi-criteria decision making based on TOPSIS.

Novel similarity measure for interval-valued data based on overlapping ratio
Presentation / Conference Contribution
Kabir, S., Wagner, C., Havens, T. C., Anderson, D. T., & Aickelin, U. (2017, July). Novel similarity measure for interval-valued data based on overlapping ratio. Presented at 2017 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE 2017), Naples, Italy

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.