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The use of fuzzy representation in a CBR system for mesh design

  • Hybrid and Novel Architectures
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Fuzzy Logic in Artificial Intelligence Towards Intelligent Systems (FLAI 1995)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 1188))

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Abstract

While knowledge-based interfaces to numerical simulation engines have generated great interest in recent years, the scaling of these systems to real-world problems has proved difficult. One reason is the knowledge acquisition task, which requires the hand-crafting of rules to cover the application domain. This research is investigating whether Case Based Reasoning (CBR) can help to overcome this problem by using previously solved problems in the solution of new problems. In this paper, we focus on the issue of knowledge representation in a CBR system for numerical simulation. A representation based on fuzzy logic is proposed, which bridges the gap between the discrete qualitative symbols with which high-level reasoning is carried out and the continuous quantitative representation used by the numerical simulation backend. We discuss the method by which this representation is used in case retrieval and describe how it is abstracted from numerical results in a solution analysis stage.

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Authors and Affiliations

  1. Hitachi Dublin Laboratory, Trinity College, Dublin 2, Ireland

    Neil Hurley

Authors
  1. Neil Hurley
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Trevor P. Martin Anca L. Ralescu

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© 1997 Springer-Verlag Berlin Heidelberg

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Hurley, N. (1997). The use of fuzzy representation in a CBR system for mesh design. In: Martin, T.P., Ralescu, A.L. (eds) Fuzzy Logic in Artificial Intelligence Towards Intelligent Systems. FLAI 1995. Lecture Notes in Computer Science, vol 1188. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-62474-0_3

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  • DOI: https://doi.org/10.1007/3-540-62474-0_3

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-62474-5

  • Online ISBN: 978-3-540-49732-5

  • eBook Packages: Springer Book Archive

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