Browsing Advanced Reasoning Group by Title

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Browsing Advanced Reasoning Group by Title

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  • Jensen, Richard (2011-12-31)
  • Jensen, Richard; Shen, Qiang (2005-01-01)
    Feature selection refers to the problem of selecting those input features that are most predictive of a given outcome; a problem encountered in many areas such as machine learning, pattern recognition and signal processing. ...
  • Jensen, Richard; Shen, Qiang (2005)
    Crisp decision trees are one of the most popular classification algorithms in current use within data mining and machine learning. However, although they possess many desirable features, they lack the ability to model ...
  • Jensen, Richard; Cornelis, Chris (2010)
    Rough set theory provides a useful mathematical foundation for developing automated computational systems that can help understand and make use of imperfect knowledge. Since its introduction, this theory has been successfully ...
  • Jensen, Richard; Cornelis, Chris (2011-12-31)
  • Cornelis, Chris; Jensen, Richard (2011-09-07)
    Nearest neighbour (NN) approaches are inspired by the way humans make decisions, comparing a test object to previously encountered samples. In this paper, we propose an NN algorithm that uses the lower and upper approximations ...
  • Verbiest, Nele; Cornelis, Chris; Jensen, Richard (IEEE, 2012)
    This paper proposes a classifier that uses fuzzy rough set theory to improve the Fuzzy Nearest Neighbour (FNN) classifier. We show that previous attempts to use fuzzy rough set theory to improve the FNN algorithm have some ...
  • Vander Heyden, Yvan; Dejaegher, Bieke; Jensen, Richard; Funar-Timofei, Simona; Goodarzi, Mohammad (2011-07-13)
    In cancer chemotherapy, multidrug resistance (MDR) is a major clinical problem which occurs by an influential mechanism and which leads to the failure of cancer chemotherapy and/or a relapse of the cancer. In this study, ...
  • Shen, Qiang; Jensen, Richard (2007)
    Attribute selection (AS) refers to the problem of selecting those input attributes or features that are most predictive of a given outcome; a problem encountered in many areas such as machine learning, pattern recognition ...
  • Shen, Qiang; Galea, Michelle (2004)
    A new approach to fuzzy rule induction from historical data is presented. The implemented system - FRANTIC - is a tested on a simple classification problem against a fuzzy tree induction algorithm, a genetic algorithm, and ...
  • Shen, Qiang (Springer Berlin Heidelberg, 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 ...
  • 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 ...
  • 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 ...
  • Snooke, Neal; Shipman, Richard (Springer, 2001-12-11)
    Model based reasoning applied to electrical systems has matured over recent years resulting in deployment of commercial design analysis tools in the automotive industry [1, 41. These tools work at the component level on ...
  • 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 ...
  • Snooke, Neal; Price, Chris (1998-11-23)
    This paper discusses the use of hierarchies of function in reasoning about automotive electrical systems. Such hierarchies enable more powerful reasoning for applications such as diagnosis, failure mode and effects analysis, ...
  • Powers, Simon; He, Jun (2008-08-01)
    Network intrusion detection is the problem of detecting unauthorised use of, or access to, computer systems over a network. Two broad approaches exist to tackle this problem: anomaly detection and misuse detection. An ...
  • 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. ...
  • Price, Chris; Snooke, Neal; Ellis, David (1999-01)
    Engineers have developed a number of design techniques in order to detect problems in their designs, such as yellow-boarding, FMECA, FTA and sneak circuit analysis. Concurrent engineering demands that all such 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 ...

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