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注册: 2010-01-10
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专业: 计算机应用技术

[交流] 【2010-05-10】国际期刊专题征稿(SCI）已有17人参与

C A L L F OR PAPERS
Special Issue on
Recent Advances in Fuzzy Qualitative Reasoning
in
International Journal of Uncertainty, Fuzziness and
Knowledge-Based Systems (IJUFKS)
Theme:
Traditionally computing has to a large degree dealt with the manipulation of numbers.
Symbolic computation has also developed in parallel, especially in Artificial Intelligence, but
often without preserving the capability of interfacing the symbolic processing of information
with numerical data. In contrast, humans employ mostly words and qualitative descriptions
when providing assessments of situations, or reasoning about complex physical or human
systems, even if a part of the data refers to numerical scales. For a long time, fuzzy sets have
been advocated by Zadeh (1973) as a methodology for interfacing numerical data about the
world, with linguistic categories or classes used in reasoning. In particular, it is the case for
fuzzy rules or fuzzy algorithms where words are interpreted as the labels of fuzzy sets.
In recent years tremendous progress has been made towards the development of formal
methods for qualitative reasoning about the behaviour of physical systems. Fuzzy Qualitative
Reasoning (FQR) is the fusion of Fuzzy Reasoning (FR) with Qualitative Reasoning (QR).
Both these research areas have as one of their goals the construction of computational
reasoning tools that can predict and explain the behaviour of, often dynamic, systems whose
analytic relations are incompletely known.
Whereas pure FR utilizes black box models, QR utilizes explicit structural models. And
whereas pure QR operates with symbolic 'quantities', FR explicitly reasons with fuzzy
intervals of varying precision that are supported directly by the real number line. The fusion
that is FQR captures the strengths of both these approaches: the integration of fuzzy set logic
with structured qualitative models enables, on the one hand, the envisionment and/or
simulation of system behaviours at higher levels of precision, and, on the other hand, the
embedding of structural knowledge into fuzzy identifiers that results in an improved
interpretability and robustness of nonlinear system identification from input-output data. In
consequence, FQR enables the successful performance of reasoning tasks, at the appropriate
levels in application domains that are particularly problematic from the modelling point of
view.
The main objective of this Special Issue is to provide an overview of the state-of-the-art in
FQR. Authors are invited to submit their original and unpublished work in this Special Issue.
The areas include, but are not limited to the following:
􀁸 Fuzzy reasoning
􀁸 Qualitative reasoning
􀁸 Reasoning under uncertainty
􀁸 Intelligent systems in robotics
􀁸 Intelligent systems in biology
􀁸 Intelligent identification of dynamical systems
􀁸 Intelligent vision detection, clustering and recognition
􀁸 Intelligent fault diagnostics and detection
􀁸 Intelligent data modelling
􀁸 Real-world applications
Manuscript Preparation and Submission:
Manuscript should conform to the standard guidelines of the International Journal of
Uncertainty, Fuzziness and Knowledge-based Systems (IJUF KS). Detailed instructions for
preparation of manuscripts can be found in the For Authors: Guidelines for Contributors at
https://www.worldscinet.com/ijufks/mkt/guidelines.shtml. Prospective authors should submit
an electronic copy of their complete manuscript via Editorial Manager web-based submission
system: https://ijufks.lip6.fr/ by 10th May 2010. "Recent Advances in Fuzzy Qualitative
Reasoning" special issue should be indicated in the corresponding cover letter. All submitted
papers will be reviewed by at least three independent reviewers.
Important Dates:
Manuscript submission deadline: 10th May, 2010
First notification: 2nd August, 2010
Revised manuscript submission: 4th October, 2010
Notification of final decision: 15th November, 2010
Final manuscript due: 13th December, 2010
Publication of the special issue: 1st Quarter 2011
Guest Editors:
Chee Seng Chan, Mimos Berhad, Kuala Lumpur, Malaysia
E-mail: cs.chan@mimos.my
George Coghill, University of Aberdeen, Aberdeen, U.K.
E-mail: g.coghill@abdn.ac.uk
Honghai Liu, University of Portsmouth, Portsmouth, U.K.
E-mail: honghai.liu@port.ac.uk

[ Last edited by xuguang.zh on 2010-3-17 at 19:35 ]

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