All Outputs (100)

DECSYS - Discrete and Ellipse-based response Capture SYStem (2019)
Presentation / Conference Contribution
Ellerby, Z., McCulloch, J., Young, J., & Wagner, C. (2019, June). DECSYS - Discrete and Ellipse-based response Capture SYStem. Presented at 2019 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE), New Orleans, LA, USA

Data-driven techniques that capture uncertainty through intervals or fuzzy sets can substantially improve systematic reasoning about uncertain information. Recent years have seen renewed interest in the capture of intervals from a variety of sources-... Read More about DECSYS - Discrete and Ellipse-based response Capture SYStem.

Fuzzy Integral Driven Ensemble Classification using A Priori Fuzzy Measures (2019)
Presentation / Conference Contribution
Agrawal, U., Wagner, C., Garibaldi, J. M., & Soria, D. (2019, June). Fuzzy Integral Driven Ensemble Classification using A Priori Fuzzy Measures. Presented at 2019 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE), New Orleans, LA, USA

Aggregation operators are mathematical functions that enable the fusion of information from multiple sources. Fuzzy Integrals (FIs) are widely used aggregation operators, which combine information in respect to a Fuzzy Measure (FM) which captures the... Read More about Fuzzy Integral Driven Ensemble Classification using A Priori Fuzzy Measures.

Leveraging IT2 Input Fuzzy Sets in Non-Singleton Fuzzy Logic Systems to Dynamically Adapt to Varying Uncertainty Levels (2019)
Presentation / Conference Contribution
Pekaslan, D., Wagner, C., & Garibaldi, J. M. (2019, June). Leveraging IT2 Input Fuzzy Sets in Non-Singleton Fuzzy Logic Systems to Dynamically Adapt to Varying Uncertainty Levels. Presented at 2019 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE), New Orleans, LA, USA

Most real-world environments are subject to different sources of uncertainty which may vary in magnitude over time. We propose that while Type-1 (T1) Non-Singleton Fuzzy Logic System (NSFLSs) have the potential to tackle uncertainty within the input... Read More about Leveraging IT2 Input Fuzzy Sets in Non-Singleton Fuzzy Logic Systems to Dynamically Adapt to Varying Uncertainty Levels.

Measuring Inter-group Agreement on zSlice Based General Type-2 Fuzzy Sets (2019)
Presentation / Conference Contribution
Navarro, J., & Wagner, C. (2019, June). Measuring Inter-group Agreement on zSlice Based General Type-2 Fuzzy Sets. Presented at 2019 IEEE International Conference on Fuzzy Systems, New Orleans, Lousiana, USA

Recently, there has been much research into modelling of uncertainty in human perception through Fuzzy Sets (FSs). Most of this research has focused on allowing respondents to express their (intra) uncertainty using intervals. Here, depending on the... Read More about Measuring Inter-group Agreement on zSlice Based General Type-2 Fuzzy Sets.

On the Relationship between Similarity Measures and Thresholds of Statistical Significance in the Context of Comparing Fuzzy Sets (2019)
Journal Article
McCulloch, J., Ellerby, Z., & Wagner, C. (2019). On the Relationship between Similarity Measures and Thresholds of Statistical Significance in the Context of Comparing Fuzzy Sets. IEEE Transactions on Fuzzy Systems, https://doi.org/10.1109/tfuzz.2019.2922161

Comparing fuzzy sets by computing their similarity is common, with a large set of measures of similarity available. However, while commonplace in the computational intelligence community, the application and results of similarity measures are less co... Read More about On the Relationship between Similarity Measures and Thresholds of Statistical Significance in the Context of Comparing Fuzzy Sets.

Paid Crowdsourcing, Low Income Contributors, and Subjectivity (2019)
Book Chapter
Haralabopoulos, G., Wagner, C., McAuley, D., & Anagnostopoulos, I. (2019). Paid Crowdsourcing, Low Income Contributors, and Subjectivity. In I. Maglogiannis, J. MacIntyre, L. Iliadis, & E. Pimenidis (Eds.), Artificial Intelligence Applications and Innovations: AIAI 2019 IFIP WG 12.5 International Workshops: MHDW and 5G-PINE 2019, Hersonissos, Crete, Greece, May 24–26, 2019, Proceedings (225-231). Springer Verlag. https://doi.org/10.1007/978-3-030-19909-8_20

Scientific projects that require human computation often resort to crowdsourcing. Interested individuals can contribute to a crowdsourcing task, essentially contributing towards the project's goals. To motivate participation and engagement, scientist... Read More about Paid Crowdsourcing, Low Income Contributors, and Subjectivity.

Combining clustering and classification ensembles: A novel pipeline to identify breast cancer profiles (2019)
Journal Article
Agrawal, U., Soria, D., Wagner, C., Garibaldi, J., Ellis, I. O., Bartlett, J. M. S., Cameron, D., Rakha, E. A., & Green, A. R. (2019). Combining clustering and classification ensembles: A novel pipeline to identify breast cancer profiles. Artificial Intelligence in Medicine, 97, 27-37. https://doi.org/10.1016/j.artmed.2019.05.002

Breast Cancer is one of the most common causes of cancer death in women, representing a very complex disease with varied molecular alterations. To assist breast cancer prognosis, the classification of patients into biological groups is of great signi... Read More about Combining clustering and classification ensembles: A novel pipeline to identify breast cancer profiles.

Similarity between interval-valued fuzzy sets taking into account the width of the intervals and admissible orders (2019)
Journal Article
Bustince, H., Marco-Detchart, C., Fernandez, J., Wagner, C., Garibaldi, J., & Takáč, Z. (2019). Similarity between interval-valued fuzzy sets taking into account the width of the intervals and admissible orders. Fuzzy Sets and Systems, https://doi.org/10.1016/j.fss.2019.04.002

In this work we study a new class of similarity measures between interval-valued fuzzy sets. The novelty of our approach lays, firstly, on the fact that we develop all the notions with respect to total orders of intervals; and secondly, on that we co... Read More about Similarity between interval-valued fuzzy sets taking into account the width of the intervals and admissible orders.

Measuring similarity between discontinuous intervals : challenges and solutions (2019)
Presentation / Conference Contribution
Kabir, S., Wagner, C., Havens, T. C., & Anderson, D. T. (2019, June). Measuring similarity between discontinuous intervals : challenges and solutions. Presented at 2019 IEEE Conference on Fuzzy Systems, New Orleans, Louisiana, USA

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 comparison of scale attributes between interval and semantic differential scales (2019)
Journal Article
Themistocleous, C., Pagiaslis, A., Smith, A., & Wagner, C. (2019). A comparison of scale attributes between interval and semantic differential scales. International Journal of Market Research, 61(4), 394-407. https://doi.org/10.1177/1470785319831227

This paper presents the results of an exploratory study comparing Interval Valued Scales (IVSs) and Semantic Differential Scales (SDSs). The paper investigates consumer perceptions regarding specific scale attributes (Preston and Colman, 2000) and ut... Read More about A comparison of scale attributes between interval and semantic differential scales.

Agent-Based Simulation Modelling for Reflecting on Consequences of Digital Mental Health (2019)
Preprint / Working Paper
Stroud, D., Wagner, C., & Siebers, P.-O. Agent-Based Simulation Modelling for Reflecting on Consequences of Digital Mental Health

The premise of this working paper is based around agent-based simulation models and how to go about creating them from given incomplete information. Agent-based simulations are stochastic simulations that revolve around groups of agents that each hav... Read More about Agent-Based Simulation Modelling for Reflecting on Consequences of Digital Mental Health.

Measuring the directional or non-directional distance between type-1 and type-2 fuzzy sets with complex membership functions (2018)
Journal Article
McCulloch, J., & Wagner, C. (2019). Measuring the directional or non-directional distance between type-1 and type-2 fuzzy sets with complex membership functions. IEEE Transactions on Fuzzy Systems, 27(7), 1506-1515. https://doi.org/10.1109/tfuzz.2018.2882342

Fuzzy sets may have complex, non-normal or non-convex membership functions that occur, for example, in the output of a fuzzy logic system or when automatically generating fuzzy sets from data. Measuring the distance between such non-standard fuzzy se... Read More about Measuring the directional or non-directional distance between type-1 and type-2 fuzzy sets with complex membership functions.

Identifying Heavy Goods Vehicle Driving Styles in the United Kingdom (2018)
Journal Article
Figueredo, G. P., Agrawal, U., Mase, J., Mesgarpour, M., Wagner, C., Soria, D., Garibaldi, J. M., Siebers, P.-O., & John, R. (2019). Identifying Heavy Goods Vehicle Driving Styles in the United Kingdom. IEEE Transactions on Intelligent Transportation Systems, 20(9), 3324-3336. https://doi.org/10.1109/TITS.2018.2875343

Although driving behaviour has been largely studied amongst private motor vehicles drivers, the literature addressing heavy goods vehicle (HGV) drivers is scarce. Identifying the existing groups of driving stereotypes and their proportions enables re... Read More about Identifying Heavy Goods Vehicle Driving Styles in the United Kingdom.

Interpretability and Complexity of Design in the Creation of Fuzzy Logic Systems — A User Study (2018)
Presentation / Conference Contribution
Rosli Razak, T. R., Garibaldi, J. M., Wagner, C., Pourabdollah, A., & Soria, D. (2018, November). Interpretability and Complexity of Design in the Creation of Fuzzy Logic Systems — A User Study. Presented at 2018 IEEE Symposium Series on Computational Intelligence (SSCI), Bangalore, India

In recent years, researchers have become increasingly more interested in designing an interpretable Fuzzy Logic System (FLS). Many studies have claimed that reducing the complexity of FLSs can lead to improved model interpretability. That is, reducin... Read More about Interpretability and Complexity of Design in the Creation of Fuzzy Logic Systems — A User Study.

Noise Parameter Estimation for Non-Singleton Fuzzy Logic Systems (2018)
Presentation / Conference Contribution
Pekaslan, D., Garibaldi, J. M., & Wagner, C. (2018, October). Noise Parameter Estimation for Non-Singleton Fuzzy Logic Systems. Presented at 2018 IEEE International Conference on Systems, Man, and Cybernetics (SMC), Miyazaki, Japan

Real-world environments face a wide range of noise (uncertainty) sources and gaining insight into the level of noise is a critical part of many applications. While Non-Singleton Fuzzy Logic Systems (NSFLSs), in particular recently introduced advanced... Read More about Noise Parameter Estimation for Non-Singleton Fuzzy Logic Systems.

A multi valued emotion lexicon created and evaluated by the crowd (2018)
Presentation / Conference Contribution
Haralabopoulos, G., Wagner, C., McAuley, D., & Simperl, E. (2018, October). A multi valued emotion lexicon created and evaluated by the crowd. Paper presented at Fifth International Conference on Social Networks Analysis, Management and Security (SNAMS-2018), Valencia, Spain

Sentiment analysis aims to uncover emotions conveyed through information. In its simplest form, it is performed on a polarity basis, where the goal is to classify information with positive or negative emotion. Recent research has explored more nuance... Read More about A multi valued emotion lexicon created and evaluated by the crowd.

SPFI: Shape-Preserving Choquet Fuzzy Integral for Non-Normal Fuzzy Set-Valued Evidence (2018)
Presentation / Conference Contribution
Havens, T. C., Pinar, A. J., Anderson, D. T., & Wagner, C. (2018, July). SPFI: Shape-Preserving Choquet Fuzzy Integral for Non-Normal Fuzzy Set-Valued Evidence. Presented at 2018 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE), Rio de Janeiro

© 2018 IEEE. Information or data aggregation is an important part of nearly all analysis problems as summarizing inputs from multiple sources is a ubiquitous goal. In this paper we propose a method for non-linear aggregation of data inputs that take... Read More about SPFI: Shape-Preserving Choquet Fuzzy Integral for Non-Normal Fuzzy Set-Valued Evidence.

Exploring subsethood to determine firing strength in non-singleton fuzzy logic systems (2018)
Presentation / Conference Contribution
Pekaslan, D., Garibaldi, J. M., & Wagner, C. (2018, July). Exploring subsethood to determine firing strength in non-singleton fuzzy logic systems. Presented at IEEE World Congress on Computational Intelligence (WCCI 2018)

Real world environments face a wide range of sources of noise and uncertainty. Thus, the ability to handle various uncertainties, including noise, becomes an indispensable element of automated decision making. Non-Singleton Fuzzy Logic Systems (NSFLS... Read More about Exploring subsethood to determine firing strength in non-singleton fuzzy logic systems.

A bidirectional subsethood based similarity measure for fuzzy sets (2018)
Presentation / Conference Contribution
Kabir, S., Wagner, C., Havens, T. C., & Anderson, D. T. (2018, July). A bidirectional subsethood based similarity measure for fuzzy sets. Presented at IEEE World Congress on Computational Intelligence (WCCI 2018)

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.

Comparison of fuzzy integral-fuzzy measure based ensemble algorithms with the state-of-the-art ensemble algorithms (2018)
Presentation / Conference Contribution
Agrawal, U., Pinar, A. J., Wagner, C., Havens, T. C., Soria, D., & Garibaldi, J. M. (2018, June). Comparison of fuzzy integral-fuzzy measure based ensemble algorithms with the state-of-the-art ensemble algorithms. Presented at 17th International Conference on Information Processing and Management of Uncertainty in Knowledge-Based Systems (IPMU 2018), Cadiz, Spain

The Fuzzy Integral (FI) is a non-linear aggregation operator which enables the fusion of information from multiple sources in respect to a Fuzzy Measure (FM) which captures the worth of both the individual sources and all their possible combinations.... Read More about Comparison of fuzzy integral-fuzzy measure based ensemble algorithms with the state-of-the-art ensemble algorithms.