• DocumentCode
    1177227
  • Title

    Multiresolutional hierarchical decision support systems

  • Author

    Meystel, A.M.

  • Author_Institution
    Dept. of Electr. & Comput. Eng., Drexel Univ., Philadelphia, PA, USA
  • Volume
    33
  • Issue
    1
  • fYear
    2003
  • Firstpage
    86
  • Lastpage
    101
  • Abstract
    Decision support systems gain better performance and higher accuracy by the virtue of building multiresolutional (multigranular, multiscale) representation, and employing multiscale behavior generation subsystem (planning and control). The latter are equipped by devices for unsupervised learning that adjust their functioning to the results of self-identification. We demonstrate that planning and learning are joint processes. The author´s intention is to emphasize that the concepts of multiresolutional representation (MR) and multiresolutional decision support (MR-DSS) probably have in common a general significance that crosses the boundaries of particular domains of applications and disciplines. The paper explores this phenomenon. The ubiquity of a principle that somehow persistently delivers benefits to many areas of knowledge and technology seems to be more important than a habit to follow the pigeonhole principle of paper presentation.
  • Keywords
    decision making; decision support systems; generalisation (artificial intelligence); knowledge management; decision support systems; dynamic programming; generalization; indistinguishability; instantiation; knowledge; knowledge management; multigranular; multiresolutional; multiresolutional decision support; multiresolutional representation; multiscale; Control systems; Decision support systems; Dynamic programming; Image edge detection; Image resolution; Paper technology; Performance gain; Process planning; Signal resolution; Unsupervised learning;
  • fLanguage
    English
  • Journal_Title
    Systems, Man, and Cybernetics, Part C: Applications and Reviews, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    1094-6977
  • Type

    jour

  • DOI
    10.1109/TSMCC.2003.809866
  • Filename
    1193064