Time series prediction and neural networks

N. Davey, S. Hunt, R. Frank

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

    1 Citation (Scopus)
    95 Downloads (Pure)

    Abstract

    Neural Network approaches to time series prediction are briefly discussed, and the need to specify an appropriately sized input window identified. Relevant theoretical results from dynamic systems theory are introduced, and the number of false neighbours heuristic is described, as a means of finding the correct embedding dimension, and thence window size. The method is applied to three time series and the resulting generalisation performance of the trained feed-forward neural network predictors is analysed. It is shown that the heuristics can provide useful information in defining the appropriate network architecture.
    Original languageEnglish
    Title of host publicationIn: Procs 5th Int Conf on Engineering Applications of Neural Networks (EANN'99)
    Pages93-98
    Publication statusPublished - 1999

    Fingerprint

    Dive into the research topics of 'Time series prediction and neural networks'. Together they form a unique fingerprint.

    Cite this