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Associated Near Sets of Merotopies

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Advances on Computational Intelligence (IPMU 2012)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 297))

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Abstract

This paper introduces associated near sets of distance functions called merotopies. An associated set of a function is a collection containing members with one or more common properties. This study has important implications in discerning patterns shared by members of an associated set. The focus in this paper is on defining and characterising distance functions relative to structures that are collections of sufficiently near (or apart) rough sets. Naimpally-Peters-Tiwari distance functions define approach spaces that are extended metric spaces. An important side-effect of this work is the discovery of various patterns that arise from the descriptions (perceptions) of associated set members. An application of the proposed approach is given in the context of camouflaged objects.

Many thanks to S. Tiwari, S. Naimpally, C.J. Henry and anonymous reviewer for their insights concerning topics in this paper. This research has been supported by the Natural Sciences and Engineering Research Council of Canada grants 185986 and 194376.

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Author information

Authors and Affiliations

  1. Computational Intelligence Laboratory, Univ. of Manitoba, E1-526, 75A Chancellor’s Circle, Winnipeg, MB, R3T 5V6, Canada

    James F. Peters & Sheela Ramanna

  2. Department of Electrical & Computer Engineering, Univ. of Manitoba, E1-526, 75A Chancellor’s Circle, Winnipeg, MB, R3T 5V6, Canada

    James F. Peters

  3. Applied Computer Science, Univ. of Winnipeg, 515 Portage Ave., Winnipeg, R3D 2E9, Canada

    Sheela Ramanna

Authors
  1. James F. Peters
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  2. Sheela Ramanna
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Editor information

Editors and Affiliations

  1. Faculty of Economics, University of Catania, Corso Italia, 55, 95129, Catania, Italy

    Salvatore Greco  & Benedetto Matarazzo  & 

  2. Université Pierre et Marie Curie - Paris6, CNRS UMR 7606, DAPA, LIP6 8, rue du Capitaine Scott, F-75015, Paris, France

    Bernadette Bouchon-Meunier

  3. Dip. Matematica e Informatica, Università di Perugia, 06123, Perugia, Italy

    Giulianella Coletti

  4. Department of Computer and Management Science, University of Trento, Via Inama 5, 38122, Trento, Italy

    Mario Fedrizzi

  5. Machine Intelligence Institute, IONA College, 10801, New Rochelle, NY, USA

    Ronald R. Yager

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© 2012 Springer-Verlag Berlin Heidelberg

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Peters, J.F., Ramanna, S. (2012). Associated Near Sets of Merotopies. In: Greco, S., Bouchon-Meunier, B., Coletti, G., Fedrizzi, M., Matarazzo, B., Yager, R.R. (eds) Advances on Computational Intelligence. IPMU 2012. Communications in Computer and Information Science, vol 297. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-31709-5_59

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  • DOI: https://doi.org/10.1007/978-3-642-31709-5_59

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-31708-8

  • Online ISBN: 978-3-642-31709-5

  • eBook Packages: Computer ScienceComputer Science (R0)

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