Uncertain nonlinear time series analysis with applications to motion analysis and epidemic spreading

Jinsheng Xie () and Waichon Lio ()
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Jinsheng Xie: Tsinghua University
Waichon Lio: Beihang University

Fuzzy Optimization and Decision Making, 2024, vol. 23, issue 2, No 6, 279-294

Abstract: Abstract Uncertain nonlinear time series analysis is a set of statistical techniques that use uncertainty theory to predict future values via nonlinear dynamics based on the previous observations. By assuming that the disturbance term is an uncertain variable, an uncertain nonlinear time series model is derived in this paper. In addition, this paper presents a method to estimate unknown parameters in an uncertain nonlinear time series model. Finally, some real examples (motion analysis and epidemic spreading) are provided to illustrate uncertain nonlinear time series analysis. As a result, it is shown that the uncertain nonlinear time series model may provide higher forecast accuracy than linear one.

Keywords: Uncertainty theory; Uncertain statistics; Uncertain time series analysis; Motion analysis; Epidemic spreading (search for similar items in EconPapers)
Date: 2024
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DOI: 10.1007/s10700-024-09421-1

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