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Partitioning the universe of discourse by information granule and forecasting in fuzzy time series

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Indexed by:期刊论文

Date of Publication:2013-01-01

Journal:ICIC Express Letters

Included Journals:EI、Scopus

Volume:7

Issue:9

Page Number:2601-2607

ISSN No.:1881803X

Abstract:Partitioning the universe of discourse and determining intervals are very important issues for forecasting in fuzzy time series. Equal length intervals used in most existing literatures are convenient but subjective to partition the universe. In this paper, the purpose of our study is to determine effective intervals with unequal length to improve forecast accuracy. A new method to determine intervals with unequal length is proposed and these intervals carry well-defined interpretability. Firstly, using fuzzy c-means clustering algorithm we calculate the prototypes of data set, and secondly, we obtain some subsets according to the distribution of the prototypes. At last, we get the effective intervals by information granules. The proposed method is evaluated using experimental data and its performance is contrasted with the equal length intervals available in the literature. Empirical results show that the proposed method can greatly improve forecast a ccuracy. ? 2013 ICIC International.

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