Outputs (81)

Modelling uncertainty in production processes using non-singleton fuzzification and fuzzy cognitive maps: a virgin olive oil case study (2016)
Presentation / Conference Contribution
Marchal, P. C., Wagner, C., Gámez, J. G., & Gómez, J. O. Modelling uncertainty in production processes using non-singleton fuzzification and fuzzy cognitive maps: a virgin olive oil case study. Presented at 2016 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE 2016)

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.

Measuring player’s behaviour change over time in public goods game (2016)
Presentation / Conference Contribution
Fattah, P., Aickelin, U., & Wagner, C. (2016, September). Measuring player’s behaviour change over time in public goods game. Presented at SAI Intelligent Systems Conference 2016, London, UK

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)
Presentation / Conference Contribution
Aladi, J. H., Wagner, C., & Pourabdollah, A. Contrasting singleton type-1 and interval type-2 non-singleton type-1 fuzzy logic systems. Presented at 2016 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE 2016)

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)
Presentation / Conference Contribution
Madi, E., Garibaldi, J. M., & Wagner, C. An exploration of issues and limitations in current methods of TOPSIS and fuzzy TOPSIS. Presented at 2016 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE)

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)
Presentation / Conference Contribution
Navarro, J., Wagner, C., & Aickelin, U. Applying interval type-2 fuzzy rule based classifiers through a cluster-based class representation. Presented at 2015 IEEE Symposium Series on Computational Intelligence

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)
Presentation / Conference Contribution
Figueredo, G. P., Wagner, C., Garibaldi, J. M., & Aickelin, U. (2015, August). Adaptive Data Communication Interface: A User-Centric Visual Data Interpretation Framework. Presented at Proceedings - 14th IEEE International Conference on Trust, Security and Privacy in Computing and Communications, TrustCom 2015, Helsinki, Finland

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.