• DocumentCode
    330293
  • Title

    An oracle based on the general regression neural network

  • Author

    Masters, Timothy ; Land, Walker H., Jr. ; Maniccam, Suchindram

  • Author_Institution
    TMAIC, Vestal, NY, USA
  • Volume
    2
  • fYear
    1998
  • fDate
    11-14 Oct 1998
  • Firstpage
    1615
  • Abstract
    The general regression neural network is well known to be an extremely effective prediction model in a wide variety of problems. It has been established that in many prediction problems, the results obtained by intelligently combining the outputs of several different prediction models are generally superior to the results obtained by using any one of the models. An overseer model that combines predictions from other independently trained prediction models is often called an oracle. The paper describes how the general regression neural network can be modified to serve as a powerful oracle for combining decisions from multiple arbitrary models
  • Keywords
    forecasting theory; neural nets; general regression neural network; oracle; overseer model; prediction model; recently; Density functional theory; Equations; Neural networks; Predictive models;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Systems, Man, and Cybernetics, 1998. 1998 IEEE International Conference on
  • Conference_Location
    San Diego, CA
  • ISSN
    1062-922X
  • Print_ISBN
    0-7803-4778-1
  • Type

    conf

  • DOI
    10.1109/ICSMC.1998.728119
  • Filename
    728119