Browsing Advanced Reasoning Group by Title

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Browsing Advanced Reasoning Group by Title

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  • Shen, Qiang; Rasmani, Khairul A. (2006-12)
    Several approaches using fuzzy techniques have been proposed to provide a practical method for evaluating student academic performance. However, these approaches are largely based on expert opinions and are difficult to ...
  • Shen, Qiang; Jensen, Richard (IGI Global, 2008)
    Data reduction is an important step in knowledge discovery from data. The high dimensionality of databases can be reduced using suitable techniques, depending on the requirements of the data mining processes. These techniques ...
  • Bell, Jonathan; Snooke, Neal (2004-08)
    Functional modeling languages have been used to describe processes that react to discrete external events and remain in a constant state until another such event stimulates a change in system state, and are deficient in ...
  • Shen, Qiang; Boongoen, Tossapon (2008-07-17)
    Combating identity fraud is prominent and urgent since false identity has become the common denominator of all serious crime. Typical approaches to detecting false identity rely on the similarity measure of text-based ...
  • Diao, Ren; Shen, Qiang (2010-09)
    Harmony search is a recently developed meta heuristic capable of solving discrete and continuous valued optimisation problems. However, the nature of pre-defined constant parameters limits the exploitation of the algorithm. ...
  • Boongoen, Tossapon; Shen, Qiang; Price, Christopher John (2010-03-01)
    Combating the identity problem is crucial and urgent as false identity has become a common denominator of many serious crimes, including mafia trafficking and terrorism. Without correct identification, it is very difficult ...
  • MacParthaláin, Neil Seosamh; Shen, Qiang; Jensen, Richard (2010-03-01)
    Feature Selection (FS) or Attribute Reduction techniques are employed for dimensionality reduction and aim to select a subset of the original features of a dataset which are rich in the most useful information. The benefits ...
  • Shen, Qiang; MacParthaláin, Neil Seosamh; Jensen, Richard (2007-07-23)
    Feature Selection (FS) is a technique for dimensionality reduction. Its aims are to select a subset of the original features of a dataset which are rich in the most useful information. The benefits include improved data ...
  • He, Jun; Yao, Xin (2001-03-15)
    The computational time complexity is an important topic in the theory of evolutionary algorithms (EAs). This paper reports some new results on the average time complexity of EAs. Based on drift analysis, some useful drift ...
  • Barnes, David Preston; Shang, Changjing; Shen, Qiang (2009)
    This paper presents a novel study of the classification of large-scale Mars McMurdo panorama image. Three dimensionality reduction techniques, based on fuzzy-rough sets, information gain ranking, and principal component ...
  • Singh, Vishal; Shen, Qiang; Galea, Michelle (2005)
    Iterative rule learning is a common strategy for fuzzy rule induction using stochastic population-based algorithms (SPBAs) such as Ant Colony Optimisation and genetic algorithms. Several SPBAs are run in succession with ...
  • Shen, Qiang; Hayes, B.; Aitken, Colin; Jensen, Richard (2007-08)
    At present, likelihood ratios for two-level models are determined with the use of a normal kernel estimation procedure when the between-group distribution is thought to be non-normal. An extension is described here for a ...
  • Fu, Xin; Shen, Qiang; Boongoen, Tossapon (2010-04-12)
    Given a set of collected evidence and a predefined knowledge base, some existing knowledge-based approaches have the capability of synthesizing plausible crime scenarios under restrictive conditions. However, significant ...
  • Shen, Qiang; Galea, Michelle (2004)
    An overview of the application of evolutionary computation to fuzzy knowledge discovery is presented. This is set in one of two contexts: overcoming the knowledge acquisition bottleneck in the development of intelligent ...
  • Miguel, Ian; Shen, Qiang (2005-03)
    This work presents an extension to qualitative simulation that enables a qualitative reasoning system to support variables that exhibit delayed reactions to their constraining functions. Information stored in the previous ...
  • MacParthaláin, Neil Seosamh; Shen, Qiang (2009-05-01)
    Of all of the challenges which face the effective application of computational intelligence technologies for pattern recognition, dataset dimensionality is undoubtedly one of the primary impediments. In order for pattern ...
  • Yang, Longzhi; Shen, Qiang (2009)
    Fuzzy interpolative reasoning strengthens the power of fuzzy inference by enhancing the robustness of fuzzy systems and reducing systems complexity. However, during the interpolation process, it is possible that multiple ...
  • Boongoen, Tossapon; Shang, Changjing; Iam-On, Natthakan; Shen, Qiang (2011-12-12)
    The measure of data reliability has recently proven useful for a number of data analysis tasks. This paper extends the underlying metric to a new problem of soft subspace clustering. The concept of subspace clustering has ...
  • Tuson, Andrew; Shen, Qiang; Jensen, Richard (2010)
    This paper describes a novel, principled approach to real-valued dataset reduction based on fuzzy and rough set theory. The approach is based on the formulation of fuzzy-rough discernibility matrices, that can be transformed ...
  • Wu, Wei; Shen, Qiang; Qu, Yanpeng; MacParthaláin, Neil Seosamh (IEEE Computational Intelligence Society, 2010-09)
    The assessment of mammographic risk analysis is an important issue in the medical field. Various approaches have been applied in order to achieve a higher accuracy in such analysis. In this paper, an approach known as ...

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