Time series granulation and forecasting based on <i>k</i>-plane clustering

YANG Xiyang; YU Fusheng

doi:10.12202/j.0476-0301.2019241

Journal of Beijing Normal University(Natural Science) > 2020 > 56(6): 751-762. > DOI: 10.12202/j.0476-0301.2019241

YANG Xiyang, YU Fusheng. Time series granulation and forecasting based on k-plane clustering[J]. Journal of Beijing Normal University(Natural Science), 2020, 56(6): 751-762. DOI: 10.12202/j.0476-0301.2019241

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Time series granulation and forecasting based on k-plane clustering

YANG Xiyang^{1, 2,},
YU Fusheng^2, ,

1.
Key Laboratory of Intelligent Computing and Information Processing of Fujian Province University, Quanzhou Normal University, 362000, Quanzhou, Fujian, China
2.
School of Mathematical Science, Beijing Normal University, 100875, Beijing, China

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Received Date: September 09, 2019
Available Online: July 21, 2020

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Abstract

Abstract

A special k-plane algorithm to cluster all data in a time series into a number of time windows of unequal-length in both time and numerical domains is designed here．In each time window, a linear fuzzy information granule is established, then piecewise linear granulation representation of original time series is obtained．We introduce a distance measure for two linear information granules of unequal size to construct prediction of granular time series based on fuzzy inference．The proposed forecasting could complete long-term prediction for time series with pseudo-period．
- granular time series,
- k-plane clustering,
- fuzzy inference system,
- forecasting

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