All Outputs (53)

Comparison of fuzzy integral-fuzzy measure based ensemble algorithms with the state-of-the-art ensemble algorithms (2018)
Conference Proceeding

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.

Visual landmark sequence-based indoor localization (2017)
Conference Proceeding

This paper presents a method that uses common objects as landmarks for smartphone-based indoor localization and navigation. First, a topological map marking relative positions of common objects such as doors, stairs and toilets is generated from floo... Read More about Visual landmark sequence-based indoor localization.

Determining firing strengths through a novel similarity measure to enhance uncertainty handling in non-singleton fuzzy logic systems (2017)
Conference Proceeding

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.

Vehicle incident hot spots identification: An approach for big data (2017)
Conference Proceeding

In this work we introduce a fast big data approach for road incident hot spot identification using Apache Spark. We implement an existing immuno-inspired mechanism, namely SeleSup, as a series of MapReduce-like operations. SeleSup is composed of a nu... Read More about Vehicle incident hot spots identification: An approach for big data.

Exploring the use of type-2 fuzzy sets in multi-criteria decision making based on TOPSIS (2017)
Conference Proceeding

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.

Type-1 and interval type-2 ANFIS: a comparison (2017)
Conference Proceeding

In a previous paper, we proposed an extended ANFIS architecture and showed that interval type-2 ANFIS produced larger errors than type-1 ANFIS on the well-known IRIS classification problem. In this paper, more experiments on both synthetic and real-w... Read More about Type-1 and interval type-2 ANFIS: a comparison.

A new dynamic approach for non-singleton fuzzification in noisy time-series prediction (2017)
Conference Proceeding

Non-singleton fuzzification is used to model uncertain (e.g. noisy) inputs within fuzzy logic systems. In the standard approach, assuming the fuzzification type is known, the observed [noisy] input is usually considered to be the core of the input fu... Read More about A new dynamic approach for non-singleton fuzzification in noisy time-series prediction.

Similarity-based non-singleton fuzzy logic control for improved performance in UAVs (2017)
Conference Proceeding

© 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.

Validation of a quantifier-based fuzzy classification system for breast cancer patients on external independent cohorts (2016)
Conference Proceeding

Recent studies in breast cancer domains have identified seven distinct clinical phenotypes (groups) using immunohistochemical analysis and a variety of unsupervised learning techniques. Consensus among the clustering algorithms has been used to categ... Read More about Validation of a quantifier-based fuzzy classification system for breast cancer patients on external independent cohorts.

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.

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.

An extended ANFIS architecture and its learning properties for type-1 and interval type-2 models (2016)
Conference Proceeding

In this paper, an extended ANFIS architecture is proposed. By incorporating an extra layer for the fuzzification process, the extended architecture is able to fit both type-1 and interval type-2 models. The learning properties of the proposed archite... Read More about An extended ANFIS architecture and its learning properties for type-1 and interval type-2 models.

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.

Adaptive Data Communication Interface: A User-Centric Visual Data Interpretation Framework (2015)
Conference Proceeding

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

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.

Tuning a multiple classifier system for side effect discovery using genetic algorithms (2014)
Conference Proceeding

In previous work, a novel supervised framework implementing a binary classifier was presented that obtained excellent results for side effect discovery. Interestingly, unique side effects were identified when different binary classifiers were used wi... Read More about Tuning a multiple classifier system for side effect discovery using genetic algorithms.

A data mining framework to model consumer indebtedness with psychological factors (2014)
Conference Proceeding

Modelling Consumer Indebtedness has proven to be a problem of complex nature. In this work we utilise Data Mining techniques and methods to explore the multifaceted aspect of Consumer Indebtedness by examining the contribution of Psychological Factor... Read More about A data mining framework to model consumer indebtedness with psychological factors.

Personalising mobile advertising based on users’ installed apps (2014)
Conference Proceeding

Mobile advertising is a billion pound industry that is rapidly expanding. The success of an advert is measured based on how users interact with it. In this paper we investigate whether the application of unsupervised learning and association rule min... Read More about Personalising mobile advertising based on users’ installed apps.

Attributes for causal inference in electronic healthcare databases (2013)
Conference Proceeding

Side effects of prescription drugs present a serious issue. Existing algorithms that detect side effects generally require further analysis to confirm causality. In this paper we investigate attributes based on the Bradford-Hill causality criteria... Read More about Attributes for causal inference in electronic healthcare databases.

Discovering sequential patterns in a UK general practice database (2012)
Conference Proceeding

The wealth of computerised medical information becoming readily available presents the opportunity to examine patterns of illnesses, therapies and responses. These patterns may be able to predict illnesses that a patient is likely to develop, allowin... Read More about Discovering sequential patterns in a UK general practice database.