Subject: CFP: Microcumputers in Civil Eng. issue on Machine Learning
From: [email-masked] (Yoram Reich)
Date: Mon, 30 Jan 1995 17:39:40 GMT
Newsgroups: comp.ai

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                     C A L L    F O R    P A P E R S
                            Special Issue of
                    Microcomputers in Civil Engineering
          Journal of Computer-Aided Civil and Infrastructure Engineering
                                  on
                            Machine Learning

    Machine learning deals with computational techniques for extracting
    knowledge from data in whatever form it is available so that this knowledge
    can be used for solving future problems. Engineering presents opportunities
    as well as challenges to machine learning. Opportunities arise from the
    wealth of data available and continually being collected and the lack of
    systematic knowledge for addressing important engineering problems. The
    challenge involves improving machine learning techniques by extending their
    usability and scope so that they can be applied to extract real engineering
    knowledge from real data.

    The issue will deal with these opportunities and challenges. It will
    include various approaches such as symbolic learning techniques, neural
    networks, genetic algorithms, or their combinations. While we encourage
    submissions in civil and infrastructure engineering, we will also include
    contributions that can be potentially applied or are relevant to these
    areas. Topics of interest include, but are not limited to:

      o  Real industrial applications of machine learning.

      o  Studies on the limitations of machine learning for engineering
         purposes, and proposals for improvements.

      o  Comparisons of different machine learning techniques on engineering
         problems.

      o  Critical and comprehensive reviews of present practice of applying
         machine learning to engineering problems.

      o  Selection criteria between machine learning techniques to match given
         application characteristics.

      o  Uses of machine learning that uncovered previously unknown engineering
         knowledge.

    Authors are requested to inform the guest editor about their intention to
    contribute to the issue by July 30, 1995.

    Important dates:
     Papers due              Nov. 30, 1995
     Notification of status  Feb. 28, 1996
     Revised papers due      May 31, 1996

    All published papers will pass the regular peer review of the journal.
    Authors should submit 4 copies of an original paper to the guest editor:

    Dr. Yoram Reich
    Department of Solid Mechanics, Materials and Structures
    Faculty of Engineering
    Tel Aviv University
    Tel Aviv 69978
    Israel
    Tel: + 972 3 6407385
    Fax: + 972 3 6429540
    Email: [email-masked]