Browsing Advanced Reasoning Group by Title

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Browsing Advanced Reasoning Group by Title

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  • 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)
    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 ...
  • 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 ...
  • Model-Based Reasoning: A Principled Approach for Software Engineering 
    Lee, Mark (2000)
    The software engineering industry suffers from almost unmanageable complexity both in the products it produces and in the processes of production. One of the current shortcomings in the software production process is the ...
  • Model-based systems in the automotive industry 
    Price, Chris; Struss, Peter (2004-01)
    The automotive industry was the first to promote the development of applications of model-based systems technology on a broad scale and, as a result, has produced some of the most advanced prototypes and products. In this ...
  • Modelling random fuzzy renewal reward processes 
    Shen, Qiang; Zhao, Ruiqing; Tang, Wansheng (2008-10)
    This short paper discusses the modeling of random fuzzy renewal reward processes in which the interarrival times and rewards are represented by nonnegative random fuzzy variables. Based on random fuzzy theory, a random ...
  • Modifying weighted fuzzy subsethood-based rule models with fuzzy quantifiers 
    Shen, Qiang; Rasmani, Khairul (2004)
    The use of fuzzy quantifiers in linguistic fuzzy models helps to build fuzzy systems that use linguistic terms in a more natural way. Although several fuzzy quantification techniques have been developed, the application ...
  • Mutation Rate Matters Even When Optimizing Monotonic Functions 
    Jansen, Thomas (2012)
    Extending previous analyses on function classes like linear functions, we analyze how the simple (1+1) evolutionary algorithm optimizes pseudo-Boolean functions that are strictly monotonic. These functions have the property ...
  • Nearest-Neighbor Guided Evaluation of Data Reliability and Its Applications 
    Boongoen, Tossapon; Shen, Qiang (2010)
    The intuition of data reliability has recently been incorporated into the main stream of research on ordered weighted averaging (OWA) operators. Instead of relying on human-guided variables, the aggregation behavior is ...
  • New approaches to fuzzy-rough feature selection 
    Shen, Qiang; Jensen, Richard (2009-08)
    There has been great interest in developing methodologies that are capable of dealing with imprecision and uncertainty. The large amount of research currently being carried out in fuzzy and rough sets is representative of ...
  • A New Approach for Analyzing Average Time Complexity of Population-Based Evolutionary Algorithms on Unimodal Problems 
    Chen, Tianshi; He, Jue; Chen, Guoliang; Yao, Xin; He, Jun (2009-10-01)
    In the past decades, many theoretical results related to the time complexity of evolutionary algorithms (EAs) on different problems are obtained. However, there is not any general and easy-to-apply approach designed ...

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