Browsing Cyfrifiadureg / Computer Science by Title

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Browsing Cyfrifiadureg / Computer Science by Title

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  • King, Ross Donald; Whelan, Kenneth Edward; Jones, Ffion M.; Reiser, Philip G. K.; Bryant, Christopher H.; Muggleton, Stephen H.; Kell, Douglas B.; Oliver, Stephen G. (2004-01-15)
    The question of whether it is possible to automate the scientific process is of both great theoretical interest and increasing practical importance because, in many scientific areas, data are being generated much faster ...
  • Jones, Andrew R.; Miller, Michael; Aebersold, Ruedi; Apweiler, Rolf; Ball, Catherine A.; Brazma, Alvis; DeGreef, James; Hardy, Nigel; Hermjakob, Henning; Hubbard, Simon J.; Hussey, Peter; Igra, Mark; Jenkins, Helen; Julian Jr, Randall K.; Laursen, Kent; Oliver, Stephen G.; Paton, Norman W.; Sansone, Susanna-Assunta; Sarkans, Ugis; Stoeckert Jr, Christian J.; Taylor, Chris F.; Whetzel, Patricia L.; White, Joseph A.; Spellman, Paul; Pizarro, Angel (2007-10-05)
    The Functional Genomics Experiment data model (FuGE) has been developed to facilitate convergence of data standards for high-throughput, comprehensive analyses in biology. FuGE models the components of an experimental ...
  • Dobson, Paul D.; Smallbone, Kieran; Jameson, Daniel; Simeonidis, Evangelos; Lanthaler, Karin; Pir, Pınar; Lu, Chuan; Swainston, Neil; Dunn, Warwick B.; Fisher, Paul; Hull, Duncan; Brown, Marie; Oshota, Olusegun; Stanford, Natalie J.; Kell, Douglas B.; King, Ross Donald; Oliver, Stephen G.; Stevens, Robert D.; Mendes, Pedro (2010-10-28)
    Background. To date, several genome-scale network reconstructions have been used to describe the metabolism of the yeast Saccharomyces cerevisiae, each differing in scope and content. The recent community-driven reconstruction, ...
  • Fu, X.; Shen, Q. (2011-07)
    There are a variety of measures to describe classification performance with respect to different criteria and they are often represented by numerical values. Psychologists have commented that human beings can only reasonably ...
  • Fu, Xin; Shen, Qiang (2010-08)
    Automated modeling refers to automatic (re-)formulation of alternative system models that embody the simplification, abstraction, and approximation of knowledge and data for a given task. This technique is highly desirable ...
  • Shen, Qiang; Yang, M. (2008)
    This paper presents a fuzzy knowledge-based system for turbomachinery diagnosis. Given symptoms associated with a vibration problem, the system can identify and rank possible causes by performing incremental forward chaining. ...
  • MacParthaláin, Neil Seosamh; Jensen, Richard; Shen, Qiang (2006-07-26)
    Feature Selection (FS) is a dimensionality reduction technique that aims to select a subset of the original features of a dataset which offer the most useful information. The benefits of feature selection include improved ...
  • Huang, Zhiheng; Shen, Qiang (2008-02-26)
    Fuzzy interpolation does not only help to reduce the complexity of fuzzy models, but also makes inference in sparse rule-based systems possible. It has been successfully applied to systems control, but limited work exists ...
  • Shen, Qiang; Huang, Zhiheng (2004)
    Fuzzy interpolative reasoning offers the potential to model problems using sparse rule bases, as opposed to dense rule bases deployed in traditional fuzzy systems. It thus supports the simplification of complex fuzzy models ...
  • Shen, Qiang; Huang, Zhiheng (2006-04)
    Interpolative reasoning does not only help reduce the complexity of fuzzy models but also makes inference in sparse rule-based systems possible. This paper presents an interpolative reasoning method by means of scale and ...
  • Shen, Qiang; Fu, Xin (2008-06-01)
    Given a set of collected evidence and a knowledge base, Fuzzy Compositional Modelling (FCM) begins by retrieving model fragments which are the most likely to be relevant to the available data. Since FCM often involves ...
  • Shen, Qiang; Boongoen, Tossapon; Price, Chris (Qualitative Reasoning, 2011-09-27)
    Numerical link-based similarity techniques have proven effective for identifying similar objects in the Internet and publication domains. However, for cases involving unduly high similarity measures, these methods usually ...
  • Boongoen, Tossapon; Shen, Qiang; Price, Christopher John (2011-06)
    Many approaches have been developed for academic performance evaluation using various fuzzy techniques. Initial methods rely greatly on experts' specification of analytical parameters, without making use of valuable ...
  • Liu, Honghai; Coghill, George; Barnes, Dave (2009-12)
    This paper presents a fuzzy qualitative representation of conventional trigonometry with the goal of bridging the gap between symbolic cognitive functions and numerical sensing & control tasks in the domain of physical ...
  • MacParthaláin, Neil Seosamh; Jensen, Richard; Shen, Qiang; Zwiggelaar, Reyer (2010-03-15)
    The accuracy of methods for the assessment of mammographic risk analysis is heavily related to breast tissue characteristics. Previous work has demonstrated considerable success in developing an automatic breast tissue ...
  • Jensen, Richard; Shen, Qiang (2004)
    Due to the explosive growth of electronically stored information, automatic methods must be developed to aid users in maintaining and using this abundance of information effectively. In particular, the sheer volume of ...
  • Diao, Ren; Shen, Qiang (IEEE, 2011-09-06)
    Classifier ensembles constitute one of the main research directions in machine learning and data mining. Ensembles allow higher accuracy to be achieved which is otherwise often not achievable with a single classifier. A ...
  • 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 ...

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