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Exploring How Component Factors and Their Uncertainty Affect Judgements of Risk in Cyber-Security (2019)
Conference Proceeding
Ellerby, Z., McCulloch, J., Wilson, M., & Wagner, C. (2020). Exploring How Component Factors and Their Uncertainty Affect Judgements of Risk in Cyber-Security. In Critical Information Infrastructures Security: 14th International Conference, CRITIS 2019, Linköping, Sweden, September 23–25, 2019, Revised Selected Papers (31-42). https://doi.org/10.1007/978-3-030-37670-3_3

Subjective judgements from experts provide essential information when assessing and modelling threats in respect to cyber-physical systems. For example, the vulnerability of individual system components can be described using multiple factors, such a... Read More about Exploring How Component Factors and Their Uncertainty Affect Judgements of Risk in Cyber-Security.

A Measure of Structural Complexity of Hierarchical Fuzzy Systems Adapted from Software Engineering (2019)
Conference Proceeding
Razak, T. R., Garibaldi, J. M., & Wagner, C. (2019). A Measure of Structural Complexity of Hierarchical Fuzzy Systems Adapted from Software Engineering. In 2019 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE) ( 1-7). https://doi.org/10.1109/FUZZ-IEEE.2019.8859011

Hierarchical fuzzy systems (HFSs) have been seen as an effective approach to reduce the complexity of fuzzy logic systems (FLSs), largely as a result of reducing the number of rules. However, it is not clear completely how complexity of HFSs can be m... Read More about A Measure of Structural Complexity of Hierarchical Fuzzy Systems Adapted from Software Engineering.

On the Choice of Similarity Measures for Type-2 Fuzzy Sets (2019)
Journal Article
McCulloch, J., & Wagner, C. (2020). On the Choice of Similarity Measures for Type-2 Fuzzy Sets. Information Sciences, 510, 135-154. https://doi.org/10.1016/j.ins.2019.09.027

Similarity measures are among the most common methods of comparing type-2 fuzzy sets and have been used in numerous applications. However, deciding how to measure similarity and choosing which existing measure to use can be difficult. Whilst some mea... Read More about On the Choice of Similarity Measures for Type-2 Fuzzy Sets.

ADONiS - Adaptive Online Non-Singleton Fuzzy Logic Systems (2019)
Journal Article
Pekaslan, D., Wagner, C., & Garibaldi, J. M. (2020). ADONiS - Adaptive Online Non-Singleton Fuzzy Logic Systems. IEEE Transactions on Fuzzy Systems, 28(10), 2302-2312. https://doi.org/10.1109/tfuzz.2019.2933787

Non-Singleton Fuzzy Logic Systems (NSFLSs) have the potential to capture and handle input noise within the design of input fuzzy sets. In this paper, we propose an online learning method which utilises a sequence of observations to continuously updat... Read More about ADONiS - Adaptive Online Non-Singleton Fuzzy Logic Systems.

Leveraging IT2 Input Fuzzy Sets in Non-Singleton Fuzzy Logic Systems to Dynamically Adapt to Varying Uncertainty Levels (2019)
Conference Proceeding
Pekaslan, D., Wagner, C., & Garibaldi, J. M. (2019). Leveraging IT2 Input Fuzzy Sets in Non-Singleton Fuzzy Logic Systems to Dynamically Adapt to Varying Uncertainty Levels. In 2019 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE) (1-7). https://doi.org/10.1109/FUZZ-IEEE.2019.8858800

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.

Fuzzy Integral Driven Ensemble Classification using A Priori Fuzzy Measures (2019)
Conference Proceeding
Agrawal, U., Wagner, C., Garibaldi, J. M., & Soria, D. (2019). Fuzzy Integral Driven Ensemble Classification using A Priori Fuzzy Measures. In 2019 IEEE International Conference on Fuzzy Systems (1-7). https://doi.org/10.1109/FUZZ-IEEE.2019.8858821

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.

DECSYS - Discrete and Ellipse-based response Capture SYStem (2019)
Conference Proceeding
Ellerby, Z., McCulloch, J., Young, J., & Wagner, C. (2019). DECSYS - Discrete and Ellipse-based response Capture SYStem. . https://doi.org/10.1109/FUZZ-IEEE.2019.8858996

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.

On Comparing and Selecting Approaches to Model Interval-Valued Data as Fuzzy Sets (2019)
Conference Proceeding
McCulloch, J., Ellerby, Z., & Wagner, C. (2019). On Comparing and Selecting Approaches to Model Interval-Valued Data as Fuzzy Sets. In 2019 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE) (1-6). https://doi.org/10.1109/FUZZ-IEEE.2019.8858993

The capture of interval-valued data is becoming an increasingly common approach in data collection (from survey based research to the collation of sensor data) as an efficient method of obtaining information about uncertainty associated with the data... Read More about On Comparing and Selecting Approaches to Model Interval-Valued Data as Fuzzy Sets.

Measuring Inter-group Agreement on zSlice Based General Type-2 Fuzzy Sets (2019)
Conference Proceeding
Navarro, J., & Wagner, C. (2019). Measuring Inter-group Agreement on zSlice Based General Type-2 Fuzzy Sets

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., …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)
Conference Proceeding
Kabir, S., Wagner, C., Havens, T. C., & Anderson, D. T. (2019). Measuring similarity between discontinuous intervals : challenges and solutions. In Proceedings of 2019 IEEE Conference on Fuzzy Systems

Discontinuous intervals (DIs) arise in a wide range of contexts, from real world data capture of human opinion to ?-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)
Working Paper
Stroud, D., Wagner, C., & Siebers, P. 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.