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  • 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 ...
  • A language for functional interpretation of model based simulation 
    Bell, Jonathan; Snooke, Neal; Price, Chris (2005-08)
    Functional modeling is in use for the interpretation of the results of model based simulation of engineered systems for design analysis, enabling the automatic generation of a textual design analysis report that expresses ...
  • A layered approach to automated electrical safety analysis in automotive environments 
    Price, Chris; Snooke, Neal; Lewis, Stuart (2006-06)
    Software support for the automotive electrical design process is vital, as many of the safety analysis tasks needing to be carried out, while complex, are repetitive and time consuming. Such support is required throughout ...
  • 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 ...
  • Lessons from engineering: can software benefit from product based evidence of quality? 
    Snooke, Neal (2010-08-04)
    This paper argues that software engineering should not overlook the lessons learned by other engineering disciplines with longer established histories. As software engineering evolves it should focus not only on application ...
  • 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 
    Rasmani, Khairul A.; Garibaldi, Jonathan M.; Shen, Qiang; Ellis, Ian O. (IEEE, 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 ...
  • A Link-Based Approach to the Cluster Ensemble Problem 
    Iam-On, N.; Boongoen, Tossapon; Garrett, Simon Martin; Price, Christopher John (2011-12)
    Cluster ensembles have recently emerged as a powerful alternative to standard cluster analysis, aggregating several input data clusterings to generate a single output clustering, with improved robustness and stability. ...
  • 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 (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 ...
  • 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 ...
  • Methods to accelerate the learning of bayesian network structures 
    Shen, Qiang; Daly, Ronan (2007)
    Bayesian networks have become a standard technique in the representation of uncertain knowledge. This paper proposes methods that can accelerate the learning of a Bayesian network structure from a data set. These methods ...
  • A Mixed Strategy for Evolutionary Programming Based on Local Fitness Landscape 
    Liang, Shen; He, Jun (2010-07)
    The performance of Evolutionary Programming (EP) is affected by many factors (e.g. mutation operators and selection strategies). Although the conventional approach with Gaussian mutation operator may be efficient, the ...

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