All Outputs (46)

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?.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.