## 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 language | English (US) |
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Title of host publication | Industrial Engineering Research - Conference Proceedings |

Place of Publication | Norcross, GA, United States |

Publisher | IIE |

Pages | 1025-1032 |

Number of pages | 8 |

State | Published - 1995 |

Externally published | Yes |

Event | Proceedings of the 1995 4th Industrial Engineering Research Conference - Nashville, TN, USA Duration: May 24 1995 → May 25 1995 |

### Other

Other | Proceedings of the 1995 4th Industrial Engineering Research Conference |
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City | Nashville, TN, USA |

Period | 5/24/95 → 5/25/95 |

## ASJC Scopus subject areas

- Industrial and Manufacturing Engineering