Browsing Advanced Reasoning Group by Title

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  • Fuzzy Sets and Rough Sets for Scenario Modelling and Analysis 
    Shen, Qiang (2009)
    Both fuzzy set theory and rough set theory play an important role in data-driven, systems modelling and analysis. They have been successfully applied to building various intelligent decision support systems (amongst many ...
  • A fuzzy-XCS classifier system with linguistic hedges 
    Marin-Blázquez, Javier; Shen, Qiang (2008)
    Many real-world problems require the development and application of algorithms that automatically generate human interpretable knowledge from historical data. Most existing algorithms for rule induction from imprecise data ...
  • Generalisation of Scale and Move Transformation-Based Fuzzy Interpolation 
    Shen, Qiang; Longzhi, Yang (2011)
    Fuzzy interpolative reasoning has been extensively studied due to its ability to enhance the robustness of fuzzy systems and reduce system complexity. In particular, the scale and move transformation-based approach is able ...
  • Granularity and disaggregation in compositional modelling with applications to ecological systems 
    Keppens, Jeroen; Shen, Qiang (2006-12)
    In the past decade, compositional modelling (CM) has established itself as the predominant knowledge-based approach to construct mathematical (simulation) models automatically. Although it is mainly applied to physical ...
  • Hybrid Fuzzy-Rough Rule Induction and Feature Selection 
    Cornelis, Chris; Jensen, Richard; Shen, Qiang (2009)
    The automated generation of feature pattern-based if-then rules is essential to the success of many intelligent pattern classifiers, especially when their inference results are expected to be directly human-comprehensible. ...
  • Identifying Novice Difficulties in Object Orientated Design 
    Thomasson, Benjy; Thomas, Lynda; Ratcliffe, Mark (2006)
    We report on a study of novice programmers’ object oriented class designs. These designs were analysed to discover what faults could be discovered. The two most common faults related to non-referenced classes (inability ...
  • Intelligent Hybrid Approach to False Identity Detection 
    Boongoen, Tossapon; Shen, Qiang (2009)
    Combating identity fraud is prominent and urgent since false identity has become the common denominator of all serious crime. Among many identified identity attributes, personal names are commonly falsified or aliased by ...
  • Intelligent systems for decision support 
    Shen, Qiang (2009)
    Decision support systems play an important role in many application domains. For instance, in the detection of serious crime, including terrorist activity, an intelligent system which is capable of automated modelling and ...
  • Interval-valued Fuzzy-Rough Feature Selection and Application for Handling Missing Values in Datasets 
    Shen, Qiang; Jensen, Richard (2008)
    One of the many successful applications of rough set theory has been to the area of feature selection. The rough set ideology of using only the supplied data and no other information has many benefits, where most other ...
  • Interval-valued Fuzzy-Rough Feature Selection in Datasets with Missing Values 
    Jensen, Richard; Shen, Qiang (2009)
    One of the many successful applications of rough set theory has been to the area of feature selection. The rough set principle of using only the supplied data and no other information has many benefits, where most other ...
  • Iterative vs Simultaneous Fuzzy Rule Induction 
    Galea, Michelle; Shen, Qiang (2005)
    Iterative rule learning is a common strategy for fuzzy rule induction using stochastic population-based algorithms (SPBAs) such as Ant Colony Optimisation (ACO) and genetic algorithms. Several SPBAs are run in succession ...
  • Knowledge representation for fuzzy model composition 
    Fu, Xin; Shen, Qiang (2007-06)
    Compositional Modelling (CM) has been applied to synthesize automatically plausible scenarios in many problem domains with promising results. However, due to the lack of capability to deal with imprecise or illdefined ...
  • Learning Bayesian network equivalence classes with ant colony optimization 
    Daly, Ronan; Shen, Qiang (2009-06)
    Bayesian networks are a useful tool in the representation of uncertain knowledge. This paper proposes a new algorithm called ACO-E, to learn the structure of a Bayesian network. It does this by conducting a search through ...
  • Learning Bayesian networks: approaches and issues 
    Daly, Ronan; Shen, Qiang; Aitken, Stuart (2011-05)
    Bayesian networks have become a widely used method in the modelling of uncertain knowledge. Owing to the difficulty domain experts have in specifying them, techniques that learn Bayesian networks from data have become ...
  • Linguistic hedges for ant-generated rules 
    Shen, Qiang; Galea, Michelle (2006)
    FRANTIC, a system inspired by insect behaviour for inducing fuzzy IF-THEN rules, is enhanced to produce rules with linguistic hedges. FRANTIC is evaluated against an earlier version of itself and against several other fuzzy ...
  • Linguistic probabilities: theory and application 
    Halliwell, Joe; Shen, Qiang (2009-01)
    Over the past two decades a number of different approaches to “fuzzy probabilities” have been presented. The use of the same term masks fundamental differences. This paper surveys these different theories, contrasting and ...
  • Linguistic Rulesets Extracted from a Quantifier-based Fuzzy Classification System 
    Shen, Qiang; Ellis, Ian O.; Garibaldi, Jonathan M.; Rasmani, Khairul A. (2009-08)
    The use of linguistic rulesets is considered one of the greatest advantages that fuzzy classification systems can offer compared to non-fuzzy classification systems. This paper proposes the use of fuzzy thresholds and fuzzy ...
  • Many-Valued Logic and Qualitative Modelling of Electrical Circuits 
    Lee, Mark (2000-06)
    Over the past three decades, tactile sensing has developed into a sophisticated technology. There has been a longstanding and widely held expectation that tactile sensors would have a major impact on industrial robotics ...
  • Measures for unsupervised fuzzy-rough feature selection 
    MacParthaláin, Neil Seosamh; Jensen, Richard (2010)
    For supervised learning, feature selection algorithms attemptto maximise a given function of predictive accuracy.This function usually considers the ability of feature vectorsto reflect decision class labels. It is therefore ...
  • Measures for Unsupervised Fuzzy-Rough Feature Selection 
    MacParthaláin, Neil Seosamh; Jensen, Richard (IEEE, 2009-11-30)
    For supervised learning, feature selection algorithms attempt to maximise a given function of predictive accuracy. This function usually considers the ability of feature vectors to reflect decision class labels. It is ...

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