Browsing Advanced Reasoning Group by Title

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Browsing Advanced Reasoning Group by Title

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  • Many-Valued Logic and Qualitative Modelling of Electrical Circuits 
    Lee, Mark (2000-06)
    Over the past three decades, tactile sensing has developed into a sophisticated technology. There has been a longstanding and widely held expectation that tactile sensors would have a major impact on industrial robotics ...
  • Measures for unsupervised fuzzy-rough feature selection 
    MacParthaláin, Neil Seosamh; Jensen, Richard (2010)
    For supervised learning, feature selection algorithms attemptto maximise a given function of predictive accuracy.This function usually considers the ability of feature vectorsto reflect decision class labels. It is therefore ...
  • Measures for Unsupervised Fuzzy-Rough Feature Selection 
    MacParthaláin, Neil Seosamh; Jensen, Richard (IEEE, 2009-11-30)
    For supervised learning, feature selection algorithms attempt to maximise a given function of predictive accuracy. This function usually considers the ability of feature vectors to reflect decision class labels. It is ...
  • Methods to accelerate the learning of bayesian network structures 
    Shen, Qiang; Daly, Ronan (2007)
    Bayesian networks have become a standard technique in the representation of uncertain knowledge. This paper proposes methods that can accelerate the learning of a Bayesian network structure from a data set. These methods ...
  • Model-Based Reasoning: A Principled Approach for Software Engineering 
    Lee, Mark (2000)
    The software engineering industry suffers from almost unmanageable complexity both in the products it produces and in the processes of production. One of the current shortcomings in the software production process is the ...
  • Model-based systems in the automotive industry 
    Price, Chris; Struss, Peter (2004-01)
    The automotive industry was the first to promote the development of applications of model-based systems technology on a broad scale and, as a result, has produced some of the most advanced prototypes and products. In this ...
  • Modelling random fuzzy renewal reward processes 
    Shen, Qiang; Zhao, Ruiqing; Tang, Wansheng (2008-10)
    This short paper discusses the modeling of random fuzzy renewal reward processes in which the interarrival times and rewards are represented by nonnegative random fuzzy variables. Based on random fuzzy theory, a random ...
  • Modifying weighted fuzzy subsethood-based rule models with fuzzy quantifiers 
    Shen, Qiang; Rasmani, Khairul (2004)
    The use of fuzzy quantifiers in linguistic fuzzy models helps to build fuzzy systems that use linguistic terms in a more natural way. Although several fuzzy quantification techniques have been developed, the application ...
  • Mutation Rate Matters Even When Optimizing Monotonic Functions 
    Jansen, Thomas (2012)
    Extending previous analyses on function classes like linear functions, we analyze how the simple (1+1) evolutionary algorithm optimizes pseudo-Boolean functions that are strictly monotonic. These functions have the property ...
  • Nearest-Neighbor Guided Evaluation of Data Reliability and Its Applications 
    Boongoen, Tossapon; Shen, Qiang (2010)
    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 ...
  • New approaches to fuzzy-rough feature selection 
    Shen, Qiang; Jensen, Richard (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 ...
  • A New Approach for Analyzing Average Time Complexity of Population-Based Evolutionary Algorithms on Unimodal Problems 
    Chen, Tianshi; He, Jue; Chen, Guoliang; Yao, Xin; He, Jun (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 ...
  • A New Approach to Fuzzy-Rough Nearest Neighbour Classification 
    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 ...
  • A New Approach to Fuzzy-Rough Nearest Neighbour Classification 
    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 ...
  • A Noise-tolerant Approach to Fuzzy-Rough Feature Selection 
    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 ...
  • A Novel Framework of Fuzzy Complex Numbers and its Application to Compositional Modelling 
    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, ...
  • On Models, Modelling and the Distinctive Nature of Model-Based Reasoning 
    Lee, Mark (1999)
    What are models and how is the relatively new technology of Model-Based Reasoning different from conventional modelling in science and engineering? These questions are explored in this paper by examining the fundamental ...
  • On the use of qualitative reasoning to simulate and identify metabolic pathways 
    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 ...
  • Ordered Weighted Average Based Fuzzy Rough Sets 
    Jensen, Richard; Verbiest, Nele; Cornelis, Chris (2010-10)
    Traditionally, membership to the fuzzy-rough lower, resp. upper approximation is determined by looking only at the worst, resp. best performing object. Consequently, when applied to data analysis problems, these approximations ...
  • Order-of-magnitude based link analysis for false identity detection 
    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 ...

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