Estimating fractal dimension, with application to production systems

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

1 Scopus citations

Abstract

Calculating the fractal dimension of a time series can be useful in that it: (a) gives an indication as to how many state variables are influencing the process output, (b) can be used to reject a null hypothesis that the system is random, (c) can be used as a descriptive statistic, and (d) it may indicate that some short term prediction is possible. Existing methods for calculating fractal dimension are based on topological approaches. Experiments are shown here which instead utilize nonlinear time series methods to model dynamical systems, and estimate fractal dimension. Simulations of a simple production system indicate when such systems may be chaotic as opposed to random.

Original languageEnglish (US)
Title of host publicationIndustrial Engineering Research - Conference Proceedings
Place of PublicationNorcross, GA, United States
PublisherIIE
Pages1025-1032
Number of pages8
StatePublished - 1995
Externally publishedYes
EventProceedings of the 1995 4th Industrial Engineering Research Conference - Nashville, TN, USA
Duration: May 24 1995May 25 1995

Other

OtherProceedings of the 1995 4th Industrial Engineering Research Conference
CityNashville, TN, USA
Period5/24/955/25/95

ASJC Scopus subject areas

  • Industrial and Manufacturing Engineering

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