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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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