Browsing Advanced Reasoning Group by Title

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  • 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 ...
  • Yang, M.; Shen, Qiang (2008-05-15)
    This paper presents an integrated knowledge-based system, which combines fuzzy rule-based reasoning with case-based reasoning, for turbomachinery diagnosis. By incorporating a case-based reasoning sub-system in a fuzzy ...
  • Shen, Qiang; Zhao, Ruiqing (2010-11-15)
    This paper presents a novel approach for assessing the potential risk of serious crime events (e.g. terrorist attack). The modelling and assessment of such risk is carried out under uncertain circumstances because of both ...
  • Shen, Qiang; MacParthaláin, Neil Seosamh; Jensen, Richard (2008-09-10)
    The accuracy of methods for the detection of mammographic abnormaility is heavily related to breast tissue characteristics. A breast with high tissue density will have reduced sensitivity in terms of detection. Also, breast ...
  • Shen, Qiang (Springer Nature, 2007)
    The last two decades have seen many powerful classification systems being built for large-scale real-world applications. However, for all their accuracy, one of the persistent obstacles facing these systems is that of data ...
  • Jensen, Richard; Shen, Qiang (Information Science Reference, 2007-11-15)
    Feature selection aims to determine a minimal feature subset from a problem domain while retaining a suitably high accuracy in representing the original features. Rough set theory (RST) has been used as such a tool with ...
  • Wang, Xiangyang; Yang, Jie; Jensen, Richard; Liu, Xiaojun (2006-08-08)
    The degree of malignancy in brain glioma is assessed based on Magnetic Resonance Imaging (MRI) findings and clinical data before operation. These data contain irrelevant features, while uncertainties and missing values ...
  • Shen, Qiang; Jensen, Richard (2007)
    Rough set theory provides a useful mathematical foundation for developing automated computational systems that can help understand and make use of imperfect knowledge. Despite its recency, the theory and its extensions ...
  • Zhou, Yuren; He, Jun (2007-10)
    Although there are many evolutionary algorithms (EAs) for solving constrained optimization problems, there are few rigorous theoretical analyses. This paper presents a time complexity analysis of EAs for solving constrained ...
  • Thomas, Lynda; Thomasson, Benjy; Ratcliffe, Mark (2004)
    This paper describes a project being undertaken at the University of Wales, Aberystwyth that aims to enhance the pedagogical process through the use of collaborative design. It describes a survey that highlights dissatisfaction ...
  • Huang, Zhiheng; Shen, Qiang (2004)
    This paper generalises the previously proposed interpolative reasoning method [5] to cover interpolations involving complex polygon, Gaussian or other bell-shaped fuzzy membership functions. This can be achieved by the ...
  • Shen, Qiang; Keppens, Jeroen; Aitken, Colin; Schafer, Burkhard; Lee, Mark (2007-01-16)
    Consideration of a wide range of plausible crime scenarios during any crime investigation is important to seek convincing evidence and hence to minimize the likelihood of miscarriages of justice. It is equally important ...
  • Shen, Qiang; Jensen, Richard (2004-07)
    One of the main obstacles facing current intelligent pattern recognition applications is that of dataset dimensionality. To enable these systems to be effective, a redundancy-removing step is usually carried out beforehand. ...
  • Jensen, Richard; Shen, Qiang (2004)
    Semantics-preserving dimensionality reduction 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 ...
  • Shen, Qiang; Boongoen, Tossapon (2009-08)
    Within the past decades, many fuzzy aggregationtechniques, ordered weighted averaging (OWA) in particular, have proven effective for a wide range of information processing tasks, such as decision making, image analysis, ...
  • Snooke, Neal (1999-01-01)
    Automotive electrical and electronic systems have become very sophisticated in a relatively short time. This complexity has both led to the increased need for design analysis tools and the need for these tools to deal with ...
  • Galea, Michelle; Shen, Qiang (Springer Nature, 2006)
    An approach based on Ant Colony Optimisation for the induction of fuzzy rules is presented. Several Ant Colony Optimisation algorithms are run simultaneously, with each focusing on finding descriptive rules for a specific ...
  • Daly, Ronan; Aitken, Stuart; Shen, Qiang (2006)
    For some time, learning Bayesian networks has been both feasible and useful in many problems domains. Recently research has been done on learning equivalence classes of Bayesian networks, i.e. structures that capture all ...
  • Theile, Madeleine; Jansen, Thomas (2010-05)
    The modeling and analysis of large networks of autonomous agents is an important topic with applications in many different disciplines. One way of modeling the development of such networks is by means of an evolutionary ...

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