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Explaining time series classifiers through meaningful perturbation and optimisation (2023)
Journal Article
Meng, H., Wagner, C., & Triguero, I. (2023). Explaining time series classifiers through meaningful perturbation and optimisation. Information Sciences, 645, Article 119334. https://doi.org/10.1016/j.ins.2023.119334

Machine learning approaches have enabled increasingly powerful time series classifiers. While performance has improved drastically, the resulting classifiers generally suffer from poor explainability, limiting their applicability in critical areas. S... Read More about Explaining time series classifiers through meaningful perturbation and optimisation.

Assessing responsible innovation training (2023)
Journal Article
Stahl, B. C., Aicardi, C., Brooks, L., Craigon, P. J., Cunden, M., Burton, S. D., …Webb, H. (2023). Assessing responsible innovation training. Journal of Responsible Technology, 16, Article 100063. https://doi.org/10.1016/j.jrt.2023.100063

There is broad agreement that one important aspect of responsible innovation (RI) is to provide training on its principles and practices to current and future researchers and innovators, notably including doctoral students. Much less agreement can be... Read More about Assessing responsible innovation training.

Towards Handling Uncertainty-at-Source in AI – A Review and Next Steps for Interval Regression (2023)
Journal Article
Kabir, S., Wagner, C., & Ellerby, Z. (2023). Towards Handling Uncertainty-at-Source in AI – A Review and Next Steps for Interval Regression. IEEE Transactions on Artificial Intelligence, 1-19. https://doi.org/10.1109/TAI.2023.3234930

Most of statistics and AI draw insights through modelling discord or variance between sources (i.e., inter-source) of information. Increasingly however, research is focusing on uncertainty arising at the level of individual measurements (i.e., within... Read More about Towards Handling Uncertainty-at-Source in AI – A Review and Next Steps for Interval Regression.

Feature Importance Identification for Time Series Classifiers (2022)
Conference Proceeding
Meng, H., Wagner, C., & Triguero, I. (2022). Feature Importance Identification for Time Series Classifiers. In 2022 IEEE International Conference on Systems, Man, and Cybernetics (SMC) (3293-3298). https://doi.org/10.1109/smc53654.2022.9945205

Time series classification is a challenging research area where machine learning techniques such as deep learning perform well, yet lack interpretability. Identifying the most important features for such classifiers provides a pathway to improving th... Read More about Feature Importance Identification for Time Series Classifiers.

Alpha-cut based compositional representation of fuzzy sets and exploration of associated fuzzy set regression (2022)
Conference Proceeding
Pekaslan, D., & Wagner, C. (2022). Alpha-cut based compositional representation of fuzzy sets and exploration of associated fuzzy set regression. In IEEE World Congress on Computational Intelligence (IEEE WCCI2022). https://doi.org/10.1109/FUZZ-IEEE55066.2022.9882840

The compositional representation of data and associated statistical approaches is a powerful framework for modelling and reasoning about quantities which reflect proportions of a whole. Recently, an increasing body of work has started exploring the a... Read More about Alpha-cut based compositional representation of fuzzy sets and exploration of associated fuzzy set regression.

Visualization of Interval Regression for Facilitating Data and Model Insight (2022)
Conference Proceeding
Kabir, S., & Wagner, C. (2022). Visualization of Interval Regression for Facilitating Data and Model Insight. In 2022 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE). https://doi.org/10.1109/FUZZ-IEEE55066.2022.9882717

With growing significance of interval-valued data, interest in artificial intelligence methods tailored to this data type is similarly increasing across a range of application domains. Here, regression, i.e., the modelling of the association between... Read More about Visualization of Interval Regression for Facilitating Data and Model Insight.

Does Permitting Uncertain Estimates Help or Hinder the Wisdom of Crowds? (2022)
Conference Proceeding
Ellerby, Z., & Wagner, C. (2022). Does Permitting Uncertain Estimates Help or Hinder the Wisdom of Crowds?. In 2022 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE). https://doi.org/10.1109/FUZZ-IEEE55066.2022.9882802

This paper adds to a growing body of research into the practical utility of using interval-valued (IV) response modes to efficiently capture richer quantitative data from people-e.g., through surveys. Specifically, IV responses offer a cohesive metho... Read More about Does Permitting Uncertain Estimates Help or Hinder the Wisdom of Crowds?.

Tackling communication and analytical problems in environmental planning: Expert assessment of key definitions and their relationships (2022)
Journal Article
Wallace, K. J., Wagner, C., Pannell, D. J., Kim, M. K., & Rogers, A. A. (2022). Tackling communication and analytical problems in environmental planning: Expert assessment of key definitions and their relationships. Journal of Environmental Management, 317, Article 115352. https://doi.org/10.1016/j.jenvman.2022.115352

Inadequate definition of key terms and their relationships generates significant communication and analytical problems in environmental planning. In this work, we evaluate an ontological framework for environmental planning designed to combat these p... Read More about Tackling communication and analytical problems in environmental planning: Expert assessment of key definitions and their relationships.

Constraint reformulations for set point optimization problems using fuzzy cognitive map models (2021)
Journal Article
Garzón Casado, A., Cano Marchal, P., Wagner, C., Gómez Ortega, J., & Gámez García, J. (2022). Constraint reformulations for set point optimization problems using fuzzy cognitive map models. Optimal Control Applications and Methods, 43(3), 711-721. https://doi.org/10.1002/oca.2846

The selection of optimal set points is an important problem in modern process control. Fuzzy cognitive maps (FCMs) allow to construct models of complex processes using expert knowledge, which is particularly useful in situations where measuring the v... Read More about Constraint reformulations for set point optimization problems using fuzzy cognitive map models.

Capturing richer information: On establishing the validity of an interval-valued survey response mode (2021)
Journal Article
Ellerby, Z., Wagner, C., & Broomell, S. B. (2022). Capturing richer information: On establishing the validity of an interval-valued survey response mode. Behavior Research Methods, 54, 1240-1262. https://doi.org/10.3758/s13428-021-01635-0

Obtaining quantitative survey responses that are both accurate and informative is crucial to a wide range of fields. Traditional and ubiquitous response formats such as Likert and visual analogue scales require condensation of responses into discrete... Read More about Capturing richer information: On establishing the validity of an interval-valued survey response mode.

Do People Prefer to Give Interval-Valued or Point Estimates and Why? (2021)
Conference Proceeding
Ellerby, Z., & Wagner, C. (2021). Do People Prefer to Give Interval-Valued or Point Estimates and Why?. In Proceedings of IEEE International Conference on Fuzzy Systems (FUZZ-IEEE 2021) (1-6). https://doi.org/10.1109/FUZZ45933.2021.9494507

Capturing interval-valued, as opposed to more conventional point-valued data, offers a potentially efficient method of obtaining richer information in individual responses. In turn, interval-valued data provide a strong foundation for subsequent fuzz... Read More about Do People Prefer to Give Interval-Valued or Point Estimates and Why?.

Designing the Hierarchical Fuzzy Systems Via FuzzyR Toolbox (2021)
Conference Proceeding
Razak, T. R., Chen, C., Garibaldi, J. M., & Wagner, C. (2021). Designing the Hierarchical Fuzzy Systems Via FuzzyR Toolbox. In 2021 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE). https://doi.org/10.1109/FUZZ45933.2021.9494485

The use of Hierarchical Fuzzy Systems (HFS) has been well acknowledged as a good approach in reducing the complexity and improving the interpretability of fuzzy logic systems (FLS). Over the past years, many fuzzy logic toolkits have been made availa... Read More about Designing the Hierarchical Fuzzy Systems Via FuzzyR Toolbox.

An Extension of the FuzzyR Toolbox for Non-Singleton Fuzzy Logic Systems (2021)
Conference Proceeding
Chen, C., Zhao, Y., Wagner, C., Pekaslan, D., & Garibaldi, J. M. (2021). An Extension of the FuzzyR Toolbox for Non-Singleton Fuzzy Logic Systems. In 2021 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE). https://doi.org/10.1109/fuzz45933.2021.9494472

Recent years have seen a surge in interest in non-singleton fuzzy systems. These systems enable the direct modelling of uncertainty affecting systems' inputs using the fuzzification stage. Moreover, recent work has shown how different composition app... Read More about An Extension of the FuzzyR Toolbox for Non-Singleton Fuzzy Logic Systems.

A Fast Inference and Type-Reduction Process for Constrained Interval Type-2 Fuzzy Systems (2020)
Journal Article
D'Alterio, P., Garibaldi, J. M., John, R. I., & Wagner, C. (2021). A Fast Inference and Type-Reduction Process for Constrained Interval Type-2 Fuzzy Systems. IEEE Transactions on Fuzzy Systems, 29(11), 3323-3333. https://doi.org/10.1109/TFUZZ.2020.3018379

Constrained interval type-2 (CIT2) fuzzy sets have been introduced to preserve interpretability when moving from type-1 to interval type-2 (IT2) membership functions. Although they can be used to produce type-2 fuzzy systems with enhanced explainabil... Read More about A Fast Inference and Type-Reduction Process for Constrained Interval Type-2 Fuzzy Systems.

Choosing Sample Sizes for Statistical Measures on Interval-Valued Data (2020)
Conference Proceeding
McCulloch, J., Ellerby, Z., & Wagner, C. (2020). Choosing Sample Sizes for Statistical Measures on Interval-Valued Data. In 2020 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE) (1-8). https://doi.org/10.1109/FUZZ48607.2020.9177745

Intervals have frequently been used in the literature to represent uncertainty in data, from eliciting uncertain judgements from experts to representing uncertainty in sensor measurements. This widespread use of intervals has led to research on inter... Read More about Choosing Sample Sizes for Statistical Measures on Interval-Valued Data.

Insights from interval-valued ratings of consumer products - a DECSYS appraisal (2020)
Conference Proceeding
Ellerby, Z., Miles, O., McCulloch, J., & Wagner, C. (2020). Insights from interval-valued ratings of consumer products - a DECSYS appraisal. In 2020 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE) (1-8). https://doi.org/10.1109/FUZZ48607.2020.9177634

The capture and analysis of interval-valued data has seen increased interest over recent years. This offers a direct means to capture and reason about uncertainty in data, whether obtained from sensors or from people. Open-source software (DECSYS [1]... Read More about Insights from interval-valued ratings of consumer products - a DECSYS appraisal.

Juzzy Constrained: Software for Constrained Interval Type-2 Fuzzy Sets and Systems in Java (2020)
Conference Proceeding
D'Alterio, P., Garibaldi, J. M., John, R. I., & Wagner, C. (2020). Juzzy Constrained: Software for Constrained Interval Type-2 Fuzzy Sets and Systems in Java. In Proceedings of IEEE World Congress on Computational Intelligence (WCCI) 2020

Constrained interval type-2 (CIT2) fuzzy sets are a class of type-2 fuzzy sets that has been recently proposed as a way to extend type-1 membership functions to interval type-2 (IT2) while keeping a semantic connection between the IT2 fuzzy set and t... Read More about Juzzy Constrained: Software for Constrained Interval Type-2 Fuzzy Sets and Systems in Java.

Performance and Interpretability in Fuzzy Logic Systems – can we have both? (2020)
Conference Proceeding
Pekaslan, D., Chen, C., Wagner, C., & Garibaldi, J. M. (2020). Performance and Interpretability in Fuzzy Logic Systems – can we have both?.

Fuzzy Logic Systems can provide a good level of interpretability and may provide a key building block as part of a growing interest in explainable AI. In practice, the level of interpretability of a given fuzzy logic system is dependent on how well i... Read More about Performance and Interpretability in Fuzzy Logic Systems – can we have both?.

A Similarity Measure Based on Bidirectional Subsethood for Intervals (2020)
Journal Article
Kabir, S., Wagner, C., Havens, T. C., & Anderson, D. T. (2020). A Similarity Measure Based on Bidirectional Subsethood for Intervals. IEEE Transactions on Fuzzy Systems, 28(11), 2890-2904. https://doi.org/10.1109/tfuzz.2019.2945249

With a growing number of areas leveraging interval-valued data—including in the context of modelling human uncertainty (e.g., in Cyber Security), the capacity to accurately and systematically compare intervals for reasoning and computation is increas... Read More about A Similarity Measure Based on Bidirectional Subsethood for Intervals.

Uncertainty-Aware Forecasting of Renewable Energy Sources (2020)
Conference Proceeding
Pekaslan, D., Wagner, C., Garibaldi, J. M., Marín, L. G., & Sáez, D. (2020). Uncertainty-Aware Forecasting of Renewable Energy Sources. In 2020 IEEE International Conference on Big Data and Smart Computing (BigComp). https://doi.org/10.1109/bigcomp48618.2020.00-68

Smart grid systems are designed to enable the efficient capture and intelligent distribution of electricity across a distributed set of utilities. They are an essential component of increasingly important renewable energy sources, where it is vital t... Read More about Uncertainty-Aware Forecasting of Renewable Energy Sources.

Towards a Framework for Capturing Interpretability of Hierarchical Fuzzy Systems - A Participatory Design Approach (2020)
Journal Article
Soria, D., Razak, T. R., Garibaldi, J. M., Pourabdollah, A., & Wagner, C. (2021). Towards a Framework for Capturing Interpretability of Hierarchical Fuzzy Systems - A Participatory Design Approach. IEEE Transactions on Fuzzy Systems, 29(5), 1160-1172. https://doi.org/10.1109/tfuzz.2020.2969901

Hierarchical fuzzy systems (HFSs) have been shown to have the potential to improve the interpretability of fuzzy logic systems (FLSs). However, challenges remain, such as: "How can we measure their interpretability?", "How can we make an informed ass... Read More about Towards a Framework for Capturing Interpretability of Hierarchical Fuzzy Systems - A Participatory Design Approach.

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.

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.

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.

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.

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.

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.

Interpretability and Complexity of Design in the Creation of Fuzzy Logic Systems - A User Study (2018)
Conference Proceeding
Rosli Razak, T. R., Garibaldi, J. M., Wagner, C., Pourabdollah, A., & Soria, D. (2018). Interpretability and Complexity of Design in the Creation of Fuzzy Logic Systems - A User Study. In Proceedings of the 2018 IEEE Symposium Series on Computational Intelligence (IEEE-SSCI 2018) (420-426). https://doi.org/10.1109/SSCI.2018.8628924

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.

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., …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.

Noise Parameter Estimation for Non-Singleton Fuzzy Logic Systems (2018)
Conference Proceeding
Pekaslan, D., Garibaldi, J. M., & Wagner, C. (2018). Noise Parameter Estimation for Non-Singleton Fuzzy Logic Systems. In Proceedings - 2018 IEEE International Conference on Systems, Man, and Cybernetics (SMC) ( 2960-2965). https://doi.org/10.1109/SMC.2018.00503

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
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)

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)
Conference Proceeding
Havens, T. C., Pinar, A. J., Anderson, D. T., & Wagner, C. (2018). SPFI: Shape-Preserving Choquet Fuzzy Integral for Non-Normal Fuzzy Set-Valued Evidence. In 2018 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE) (1-6). https://doi.org/10.1109/Fuzz-Ieee.2018.8491555

© 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.

A bidirectional subsethood based similarity measure for fuzzy sets (2018)
Conference Proceeding
Kabir, S., Wagner, C., Havens, T. C., & Anderson, D. T. (2018). A bidirectional subsethood based similarity measure for fuzzy sets. In N/A

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.

Exploring subsethood to determine firing strength in non-singleton fuzzy logic systems (2018)
Conference Proceeding
Pekaslan, D., Garibaldi, J. M., & Wagner, C. (2018). Exploring subsethood to determine firing strength in non-singleton fuzzy logic systems.

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.

Comparison of fuzzy integral-fuzzy measure based ensemble algorithms with the state-of-the-art ensemble algorithms (2018)
Conference Proceeding
Agrawal, U., Pinar, A. J., Wagner, C., Havens, T. C., Soria, D., & Garibaldi, J. M. (2018). Comparison of fuzzy integral-fuzzy measure based ensemble algorithms with the state-of-the-art ensemble algorithms.

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.

Efficient binary fuzzy measure representation and Choquet integral learning (2018)
Conference Proceeding
Islam, M. A., Anderson, D. T., Du, X., Havens, T. C., & Wagner, C. (2018). Efficient binary fuzzy measure representation and Choquet integral learning. In Information Processing and Management of Uncertainty in Knowledge-Based Systems. Theory and Foundations (115-126). https://doi.org/10.1007/978-3-319-91473-2_10

The Choquet integral (ChI), a parametric function for information aggregation, is parameterized by the fuzzy measure (FM), which has 2N real-valued variables for N inputs. However, the ChI incurs huge storage and computational burden due to its expon... Read More about Efficient binary fuzzy measure representation and Choquet integral learning.

Input uncertainty sensitivity enhanced non-singleton fuzzy logic controllers for long-term navigation of quadrotor UAVs (2018)
Journal Article
Fu, C., Sarabakha, A., Kayacan, E., Wagner, C., John, R., & Garibaldi, J. M. (2018). Input uncertainty sensitivity enhanced non-singleton fuzzy logic controllers for long-term navigation of quadrotor UAVs. IEEE/ASME Transactions on Mechatronics, 23(2), 725-734. https://doi.org/10.1109/TMECH.2018.2810947

Input uncertainty, e.g., noise on the on-board camera and inertial measurement unit, in vision-based control of unmanned aerial vehicles (UAVs) is an inevitable problem. In order to handle input uncertainties as well as further analyze the interactio... Read More about Input uncertainty sensitivity enhanced non-singleton fuzzy logic controllers for long-term navigation of quadrotor UAVs.

Determining firing strengths through a novel similarity measure to enhance uncertainty handling in non-singleton fuzzy logic systems (2017)
Conference Proceeding
Pekaslan, D., Kabir, S., Wagner, C., & Garibaldi, J. M. (2017). Determining firing strengths through a novel similarity measure to enhance uncertainty handling in non-singleton fuzzy logic systems. In Proceedings of the 9th International Joint Conference on Computational Intelligence - Volume 0IJCCI (83-90). https://doi.org/10.5220/0006502000830090

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.

Linking sensory perceptions and physical properties of orange drinks (2017)
Conference Proceeding
McCulloch, J., Isaev, S., Bachour, K., Jreissat, M., Wagner, C., & Makatsoris, C. (2017). Linking sensory perceptions and physical properties of orange drinks.

This paper investigates if sensory perceptions of orange drinks (e.g., acidity, thickness, wateriness) can be linked to physical measurements (e.g., pH, particle size, density). Using this information, manufactured drinks can be tailored according to... Read More about Linking sensory perceptions and physical properties of orange drinks.

Efficient modeling and representation of agreement in interval-valued data (2017)
Conference Proceeding
Havens, T. C., Wagner, C., & Anderson, D. T. (2017). Efficient modeling and representation of agreement in interval-valued data. In 2017 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE) (1-6). https://doi.org/10.1109/FUZZ-IEEE.2017.8015466

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.

Novel similarity measure for interval-valued data based on overlapping ratio (2017)
Conference Proceeding
Kabir, S., Wagner, C., Havens, T. C., Anderson, D. T., & Aickelin, U. (2017). Novel similarity measure for interval-valued data based on overlapping ratio. In 2017 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE) (1-6). https://doi.org/10.1109/FUZZ-IEEE.2017.8015623

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.

The arithmetic recursive average as an instance of the recursive weighted power mean (2017)
Conference Proceeding
Wagner, C., Havens, T. C., & Anderson, D. T. (2017). The arithmetic recursive average as an instance of the recursive weighted power mean. In 2017 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE) (1-6). https://doi.org/10.1109/FUZZ-IEEE.2017.8015507

The aggregation of multiple information sources has a long history and ranges from sensor fusion to the aggregation of individual algorithm outputs and human knowledge. A popular approach to achieve such aggregation is the fuzzy integral (FI) which i... Read More about The arithmetic recursive average as an instance of the recursive weighted power mean.

Exploring the use of type-2 fuzzy sets in multi-criteria decision making based on TOPSIS (2017)
Conference Proceeding
Madi, E., Garibaldi, J. M., & Wagner, C. (2017). Exploring the use of type-2 fuzzy sets in multi-criteria decision making based on TOPSIS. In 2017 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE) (1-6). https://doi.org/10.1109/FUZZ-IEEE.2017.8015664

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.

Measuring behavioural change of players in public goods game (2017)
Book Chapter
Fattah, P., Aickelin, U., & Wagner, C. (2017). Measuring behavioural change of players in public goods game. In P. Fattah, U. Aickelin, & C. Wagner (Eds.), Measuring Behavioural Change of Players in Public Goods Game. Springer

In the public goods game, players can be classified into different types according to their participation in the game. It is an important issue for economists to be able to measure players’ strategy changes over time which can be considered as concep... Read More about Measuring behavioural change of players in public goods game.

Interpretability indices for hierarchical fuzzy systems (2017)
Conference Proceeding
Razak, T. R., Garibaldi, J. M., Wagner, C., Pourabdollah, A., & Soria, D. (2017). Interpretability indices for hierarchical fuzzy systems. In Proceedings of the 2017 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE) (1-6). https://doi.org/10.1109/FUZZ-IEEE.2017.8015616

© 2017 IEEE. Hierarchical fuzzy systems (HFSs) have been shown to have the potential to improve interpretability of fuzzy logic systems (FLSs). In recent years, a variety of indices have been proposed to measure the interpretability of FLSs such as t... Read More about Interpretability indices for hierarchical fuzzy systems.

Similarity-based non-singleton fuzzy logic control for improved performance in UAVs (2017)
Conference Proceeding
Fu, C., Sarabakha, A., Kayacan, E., Wagner, C., John, R., & Garibaldi, J. M. (2017). Similarity-based non-singleton fuzzy logic control for improved performance in UAVs. In Proceedings - 2017 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE) (1-6). https://doi.org/10.1109/FUZZ-IEEE.2017.8015440

© 2017 IEEE. As non-singleton fuzzy logic controllers (NSFLCs) are capable of capturing input uncertainties, they have been effectively used to control and navigate unmanned aerial vehicles (UAVs) recently. To further enhance the capability to handle... Read More about Similarity-based non-singleton fuzzy logic control for improved performance in UAVs.

Interval-valued sensory evaluation for customized beverage product formulation and continuous manufacturing (2017)
Conference Proceeding
Isaev, S., Jreissat, M., Makatsoris, C., Bachour, K., McCulloch, J., & Wagner, C. (2017). Interval-valued sensory evaluation for customized beverage product formulation and continuous manufacturing.

Understanding of consumer preferences and perceptions is a vital challenge for the food and beverage industry. Food and beverage product development is a very complex process that deals with highly uncertain factors, including consumer perceptions an... Read More about Interval-valued sensory evaluation for customized beverage product formulation and continuous manufacturing.

Measuring agreement on linguistic expressions in medical treatment scenarios (2016)
Conference Proceeding
Navarro, J., Wagner, C., Aickelin, U., Green, L., & Ashford, R. (2016). Measuring agreement on linguistic expressions in medical treatment scenarios. In 2016 IEEE Symposium Series on Computational Intelligence (SSCI) (1-8). https://doi.org/10.1109/SSCI.2016.7849895

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.

Cancer subtype identification pipeline: a classifusion approach (2016)
Conference Proceeding
Agrawal, U., Soria, D., & Wagner, C. (2016). Cancer subtype identification pipeline: a classifusion approach.

Classification of cancer patients into treatment groups is essential for appropriate diagnosis to increase survival. Previously, a series of papers, largely published in the breast cancer domain have leveraged Computational Intelligence (CI) developm... Read More about Cancer subtype identification pipeline: a classifusion approach.

Exploring differences in interpretation of words essential in medical expert-patient communication (2016)
Conference Proceeding
Navarro, J., Wagner, C., Aickelin, U., Green, L., & Robert, A. (2016). Exploring differences in interpretation of words essential in medical expert-patient communication. In 2016 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE)

In the context of cancer treatment and surgery, quality of life assessment is a crucial part of determining treatment success and viability. In order to assess it, patient-completed questionnaires which employ words to capture aspects of patients’ we... Read More about Exploring differences in interpretation of words essential in medical expert-patient communication.

A similarity-based inference engine for non-singleton fuzzy logic systems (2016)
Conference Proceeding
Wagner, C., Pourabdollah, A., McCulloch, J., John, R., & Garibaldi, J. M. (2016). A similarity-based inference engine for non-singleton fuzzy logic systems. In 2016 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE) (316-323). https://doi.org/10.1109/FUZZ-IEEE.2016.7737703

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 the similarity between zSlices general type-2 fuzzy sets with non-normal Secondary membership functions (2016)
Conference Proceeding
McCulloch, J., & Wagner, C. (2016). Measuring the similarity between zSlices general type-2 fuzzy sets with non-normal Secondary membership functions. In 2016 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE) (461-468). https://doi.org/10.1109/FUZZ-IEEE.2016.7737723

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.

Modelling uncertainty in production processes using non-singleton fuzzification and fuzzy cognitive maps: a virgin olive oil case study (2016)
Conference Proceeding
Marchal, P. C., Wagner, C., Gámez, J. G., & Gómez, J. O. (in press). Modelling uncertainty in production processes using non-singleton fuzzification and fuzzy cognitive maps: a virgin olive oil case study.

Decision support systems (DSSs) are a convenient tool to aid plant operators in the selection of process set points. Inputs to these systems for variables that are not easily measured online often come from assessments made by experts, with an associ... Read More about Modelling uncertainty in production processes using non-singleton fuzzification and fuzzy cognitive maps: a virgin olive oil case study.

A comparative study on the control of Quadcopter UAVs by using singleton and non-singleton fuzzy logic controllers (2016)
Conference Proceeding
Fu, C., Sarabakha, A., Kayacan, E., Wagner, C., John, R., & Garibaldi, J. M. (in press). A comparative study on the control of Quadcopter UAVs by using singleton and non-singleton fuzzy logic controllers.

Fuzzy logic controllers (FLCs) have extensively been used for the autonomous control and guidance of unmanned aerial vehicles (UAVs) due to their capability of handling uncertainties and delivering adequate control without the need for a precise, mat... Read More about A comparative study on the control of Quadcopter UAVs by using singleton and non-singleton fuzzy logic controllers.

Measuring player’s behaviour change over time in public goods game (2016)
Conference Proceeding
Fattah, P., Aickelin, U., & Wagner, C. (2016). Measuring player’s behaviour change over time in public goods game.

An important issue in public goods game is whether player's behaviour changes over time, and if so, how significant it is. In this game players can be classified into different groups according to the level of their participation in the public good.... Read More about Measuring player’s behaviour change over time in public goods game.

Modelling cyber-security experts' decision making processes using aggregation operators (2016)
Journal Article
Miller, S., Wagner, C., Aickelin, U., & Garibaldi, J. M. (2016). Modelling cyber-security experts' decision making processes using aggregation operators. Computers and Security, 62, 229-245. https://doi.org/10.1016/j.cose.2016.08.001

An important role carried out by cyber-security experts is the assessment of proposed computer systems, during their design stage. This task is fraught with difficulties and uncertainty, making the knowledge provided by human experts essential for su... Read More about Modelling cyber-security experts' decision making processes using aggregation operators.

Contrasting singleton type-1 and interval type-2 non-singleton type-1 fuzzy logic systems (2016)
Conference Proceeding
Aladi, J. H., Wagner, C., & Pourabdollah, A. (2016). Contrasting singleton type-1 and interval type-2 non-singleton type-1 fuzzy logic systems.

Most applications of both type-1 and type-2 fuzzy logic systems are employing singleton fuzzification due to its simplicity and reduction in its computational speed. However, using singleton fuzzification assumes that the input data (i.e., measuremen... Read More about Contrasting singleton type-1 and interval type-2 non-singleton type-1 fuzzy logic systems.

An exploration of issues and limitations in current methods of TOPSIS and fuzzy TOPSIS (2016)
Conference Proceeding
Madi, E., Garibaldi, J. M., & Wagner, C. (2016). An exploration of issues and limitations in current methods of TOPSIS and fuzzy TOPSIS.

Decision making is an important process for organizations. Common practice involves evaluation of prioritized alternatives based on a given set of criteria. These criteria conflict with each other and commonly no solution can satisfy all criteria sim... Read More about An exploration of issues and limitations in current methods of TOPSIS and fuzzy TOPSIS.

Fuzzy integral for rule aggregation in fuzzy inference systems (2016)
Journal Article
Tomlin, L., Anderson, D. T., Wagner, C., Havens, T. C., & Keller, J. M. (in press). Fuzzy integral for rule aggregation in fuzzy inference systems. Communications in Computer and Information Science, 610, https://doi.org/10.1007/978-3-319-40596-4_8

The fuzzy inference system (FIS) has been tuned and re-vamped many times over and applied to numerous domains. New and improved techniques have been presented for fuzzification, implication, rule composition and defuzzification, leaving one key compo... Read More about Fuzzy integral for rule aggregation in fuzzy inference systems.

Optimising rule-based classification in temporal data (2016)
Journal Article
Fattah, P., Aickelin, U., & Wagner, C. (2016). Optimising rule-based classification in temporal data. Zanco Journal of Pure and Applied Sciences, 28(2),

This study optimises manually derived rule-based expert system classification of objects according to changes in their properties over time. One of the key challenges that this study tries to address is how to classify objects that exhibit changes in... Read More about Optimising rule-based classification in temporal data.

Improved Uncertainty Capture for Nonsingleton Fuzzy Systems (2016)
Journal Article
Pourabdollah, A., Wagner, C., Aladi, J. H., & Garibaldi, J. M. (2016). Improved Uncertainty Capture for Nonsingleton Fuzzy Systems. IEEE Transactions on Fuzzy Systems, 24(6), 1513-1524. https://doi.org/10.1109/TFUZZ.2016.2540065

© 2016 IEEE. In nonsingleton fuzzy logic systems (NSFLSs), input uncertainties are modeled with input fuzzy sets in order to capture input uncertainty (e.g., sensor noise). The performance of NSFLSs in handling such uncertainties depends on both the... Read More about Improved Uncertainty Capture for Nonsingleton Fuzzy Systems.

Applying interval type-2 fuzzy rule based classifiers through a cluster-based class representation (2015)
Conference Proceeding
Navarro, J., Wagner, C., & Aickelin, U. (2015). Applying interval type-2 fuzzy rule based classifiers through a cluster-based class representation.

Fuzzy Rule-Based Classification Systems (FRBCSs) have the potential to provide so-called interpretable classifiers, i.e. classifiers which can be introspective, understood, validated and augmented by human experts by relying on fuzzy-set based rules.... Read More about Applying interval type-2 fuzzy rule based classifiers through a cluster-based class representation.

Adaptive Data Communication Interface: A User-Centric Visual Data Interpretation Framework (2015)
Conference Proceeding
Figueredo, G. P., Wagner, C., Garibaldi, J. M., & Aickelin, U. (2015). Adaptive Data Communication Interface: A User-Centric Visual Data Interpretation Framework. . https://doi.org/10.1109/Trustcom.2015.571

In this position paper, we present ideas about creating a next generation framework towards an adaptive interface for data communication and visualisation systems. Our objective is to develop a system that accepts large data sets as inputs and provid... Read More about Adaptive Data Communication Interface: A User-Centric Visual Data Interpretation Framework.

A comparison between two types of Fuzzy TOPSIS method (2015)
Conference Proceeding
Madi, E., Garibaldi, J. M., & Wagner, C. (2015). A comparison between two types of Fuzzy TOPSIS method.

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)
Conference Proceeding
McCulloch, J., Wagner, C., & Aickelin, U. (2014). Analysing fuzzy sets through combining measures of similarity and distance.

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)
Conference Proceeding
Hassan, D., Aickelin, U., & Wagner, C. (2014). Comparison of distance metrics for hierarchical data in medical databases.

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)
Conference Proceeding
McCulloch, J., Hinde, C., Wagner, C., & Aickelin, U. (2014). A fuzzy directional distance measure.

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)
Conference Proceeding
McCulloch, J., Wagner, C., & Aickelin, U. (2013). Measuring the directional distance between fuzzy sets.

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.

Improving security requirements adequacy: an interval type 2 fuzzy logic security assessment system
Conference Proceeding
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.

Extending similarity measures of interval type-2 fuzzy sets to general type-2 fuzzy sets
Conference Proceeding
McCulloch, J., Wagner, C., & Aickelin, U. Extending similarity measures of interval type-2 fuzzy sets to general type-2 fuzzy sets.

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.

Creating personalised energy plans: from groups to individuals using Fuzzy C Means Clustering
Conference Proceeding
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.