Browsing Advanced Reasoning Group by Title

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  • Boongoen, Tossapon; Shen, Qiang (2010-12)
    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 ...
  • Chen, Tianshi; He, Jun; Chen, Guoliang; Yao, Xin (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 ...
  • Jensen, Richard; Cornelis, Chris (2008-10-17)
    In this paper, we present a new fuzzy-rough nearest neighbour (FRNN) classification algorithm, as an alternative to Sarkar’s fuzzy-rough ownership function (FRNN-O) approach. By contrast to the latter, our method uses the ...
  • Jensen, Richard; Cornelis, Chris (2011)
    A new fuzzy-rough nearest neighbour (FRNN) classification algorithm is presented in this paper, as an alternative to Sarkar’s fuzzy-rough ownership function (FRNN-O) approach. By contrast to the latter, our method uses the ...
  • Jensen, Richard; Shen, Qiang (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 ...
  • Jensen, Richard; Cornelis, Chris (2008)
    In rough set based feature selection, the goal is to omit attributes (features) from decision systems such that objects in different decision classes can still be discerned. A popular way to evaluate attribute subsets with ...
  • Fu, Xin; Shen, Qiang (2009-08)
    Dealing with various inexact pieces of information has become an intrinsically important issue in knowledge-based reasoning, because many problem domains involve imprecise, incomplete and uncertain information. Indeed, ...
  • MacParthaláin, Neil Seosamh; Shen, Qiang (2010-12)
    Rough set theory (RST) has enjoyed an enormous amount of attention in recent years and has been applied to many real-world problems including data mining, pattern recognition, and intelligent control. Much research has ...
  • King, Ross Donald; Garrett, Simon; Coghill, George (Oxford Journals, 2005-01)
    Motivation: Perhaps the greatest challenge of modern biology is to develop accurate in silico models of cells. To do this we require computational formalisms for both simulation (how according to the model the state of the ...
  • Shen, Qiang; Boongoen, Tossapon (2009)
    Combating identity fraud is crucial and urgent as false identity has become the common denominator of all serious crime, including mafia trafficking and terrorism. Typical approaches to detecting the use of false identity ...
  • Jensen, Richard (Springer Nature, 2006)
    The main aim of feature selection is to determine a minimal feature subset from a problem domain while retaining a suitably high accuracy in representing the original features. In real world problems FS is a must due to ...
  • Shen, Qiang; Huang, Zhiheng (IEEE Press, 2009-08)
    Fuzzy interpolative reasoning plays an important role in fuzzy modelling as it not only helps to reduce the number of rules in a rule base, but also provides an inference mechanism for sparse rule bases. In interpolation, ...
  • Shen, Qiang; Huang, Zhiheng (2005)
    Fuzzy interpolative reasoning serves as an important role in fuzzy modelling as it does not only help reduce rule number but also provides an inference mechanism for sparse rule bases. The preservation of piece-wise linearity ...
  • Eckerdal, Anna; Ratcliffe, Mark; Sanders, Kate; Moström, Jan Erik; Zander, Carol; McCartney, Robert (2006)
    This paper describes Threshold Concepts, a theory of learning that distinguishes core concepts whose characteristics can make them troublesome in learning. With an eye to applying this theory in computer science, we consider ...
  • Eckerdal, Anna; Ratcliffe, Mark Bartley; Sanders, Kate; Moström, Jan Erik; Zander, Carol; McCartney, Robert (2006-09)
    This paper describes Threshold Concepts, a theory of learning that distinguishes core concepts whose characteristics can make them troublesome in learning. With an eye to applying this theory in computer science, we consider ...
  • Goodarzi, Mohammad; Jensen, Richard; Vander Heyden, Yvan (2012-12-01)
    A Quantitative Structure-Retention Relationship (QSRR) is proposed to estimate the chromatographic retention of 83 diverse drugs on a Unisphere poly butadiene (PBD) column, using isocratic elutions at pH 11.7. Previous ...
  • Price, Chris; Trave-Massuyes, Louise; Milne, Rob; Ironi, Liliana; Forbus, Kenneth; Bredeweg, Bert; Lee, Mark; Struss, Peter; Snooke, Neal; Lucas, Peter; Cavazza, Marc; Coghill, George (2006-12-04)
    This paper reviews the state of the art in model-based systems and qualitative reasoning, and considers where the field will be in twenty years time. It highlights six areas where developments in model-based systems in ...
  • Lee, Mark Howard; Garrett, Simon Martin (2000-10)
    When faced with an interface to an unknown system or device humans adopt exploratory interactive behaviour in order to gain information and insight. This paper describes a computer program which probes, observes and models ...
  • Shen, Qiang; Zhao, Ruiqing; Tang, Wansheng (2009)
    Random fuzzy theory offers an appropriate mechanism to model random fuzzy phenomena, with a random fuzzy variable defined as a function from a credibility space to a collection of random variables. Based on this theory, ...
  • Li, Shunqin; Shen, Qiang; Wansheng, Tang; Ruiqing, Zhao (2009)
    In renewal processes, fuzziness and randomness often coexist intrinsically. Based on the random fuzzy theory, a delayed renewal process with random fuzzy interarrival times is proposed in this paper. Relations between the ...

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