Advances in Intelligent and Soft Computing

Soft Methods for Integrated Uncertainty Modelling

Editors: Lawry, J., Miranda, E., Bugarin, A., Li, S., Angeles Gil, M., Grzegorzewski, P., Hryniewicz, O. (Eds.)

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About this book

This edited volume is the proceedings of the 2006 International Conference on Soft Methods in Probability and Statistics (SMPS 2006) hosted by the Artificial Intelligence Group at the University of Bristol, between 5-7 September 2006. This is the third of a series of biennial conferences organized in 2002 by the Systems Research Institute from the Polish Academy of Sciences in Warsaw, and in 2004 by the Department of Statistics and Operational Research at the University of Oviedo in Spain. These conferences provide a forum for discussion and research into the fusion of soft methods with probability and statistics, with the ultimate goal of integrated uncertainty modelling in complex systems involving human factors. In addition to probabilistic factors such as measurement error and other random effects, the modelling process often requires us to make qualitative and subject judgments that cannot easily be translated into precise probability values. Such judgments give rise to a number of different types of uncertainty including; fuzziness if they are based on linguistic information; epistemic uncertainty when their reliability is in question; ignorance when they are insufficient to identify or restrict key modelling parameters; imprecision when parameters and probability distributions can only be estimated within certain bounds. Statistical theory has not traditionally been concerned with modelling uncertainty arising in this manner but soft methods, a range of powerful techniques developed within AI, attempt to address those problems where the encoding of subjective information is unavoidable. These are mathematically sound uncertainty modelling methodologies which are complementary to conventional statistics and probability theory. Therefore, a more realistic modelling process providing decision makers with an accurate reflection of the true current state of our knowledge (and ignorance) requires an integrated framework incorporating both probability theory, statistics and soft methods. This fusion motivates innovative research at the interface between computer science (AI), mathematics and systems engineering.

Table of contents (47 chapters)

  • Generalized Theory of Uncertainty (GTU) – Principal Concepts and Ideas

    Zadeh, Lotfi A.

    Pages 3-4

  • Reasoning with Vague Probability Assessments

    Cooman, Gert de

    Pages 5-6

  • Soft Methods in Earth Systems Engineering

    Hall, Jim W.

    Pages 7-10

  • Statistical Data Processing under Interval Uncertainty: Algorithms and Computational Complexity

    Kreinovich, Vladik

    Pages 11-26

  • On Testing Fuzzy Independence

    Hryniewicz, Olgierd

    Pages 29-36

Buy this book

eBook $209.00
price for USA (gross)
  • ISBN 978-3-540-34777-4
  • Digitally watermarked, DRM-free
  • Included format: PDF
  • ebooks can be used on all reading devices
  • Immediate eBook download after purchase
Softcover $269.00
price for USA
  • ISBN 978-3-540-34776-7
  • Free shipping for individuals worldwide
  • Usually dispatched within 3 to 5 business days.
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Bibliographic Information

Bibliographic Information
Book Title
Soft Methods for Integrated Uncertainty Modelling
Editors
  • Jonathan Lawry
  • Enrique Miranda
  • Alberto Bugarin
  • Shoumei Li
  • Maria Angeles Gil
  • Przemyslaw Grzegorzewski
  • Olgierd Hryniewicz
Series Title
Advances in Intelligent and Soft Computing
Series Volume
37
Copyright
2006
Publisher
Springer-Verlag Berlin Heidelberg
Copyright Holder
Springer-Verlag Berlin Heidelberg
eBook ISBN
978-3-540-34777-4
DOI
10.1007/3-540-34777-1
Softcover ISBN
978-3-540-34776-7
Series ISSN
1867-5662
Edition Number
1
Number of Pages
X, 413
Number of Illustrations and Tables
59 b/w illustrations
Topics