Outputs (9)

Exploring How Component Factors and Their Uncertainty Affect Judgements of Risk in Cyber-Security (2019)
Presentation / Conference Contribution
Ellerby, Z., McCulloch, J., Wilson, M., & Wagner, C. (2019, September). Exploring How Component Factors and Their Uncertainty Affect Judgements of Risk in Cyber-Security. Presented at CRITIS 2019 : 14th International Conference on Critical Information Infrastructures Security, Linköping, Sweden

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.

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.

On Comparing and Selecting Approaches to Model Interval-Valued Data as Fuzzy Sets (2019)
Presentation / Conference Contribution
McCulloch, J., Ellerby, Z., & Wagner, C. (2019, June). On Comparing and Selecting Approaches to Model Interval-Valued Data as Fuzzy Sets. Presented at 2019 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE), New Orleans, LA, USA

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.

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.

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.

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.

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.

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.