All Outputs (14)

Measuring agreement on linguistic expressions in medical treatment scenarios (2016)
Conference Proceeding

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

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

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 comparative study on the control of Quadcopter UAVs by using singleton and non-singleton fuzzy logic controllers (2016)
Conference Proceeding

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.

Modelling uncertainty in production processes using non-singleton fuzzification and fuzzy cognitive maps: a virgin olive oil case study (2016)
Conference Proceeding

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 the similarity between zSlices general type-2 fuzzy sets with non-normal Secondary membership functions (2016)
Conference Proceeding

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.

A similarity-based inference engine for non-singleton fuzzy logic systems (2016)
Conference Proceeding

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 player’s behaviour change over time in public goods game (2016)
Conference Proceeding

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

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

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

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

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

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

© 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.