Research on Discourse Partition of Fuzzy Time Series Models

doi:10.3969/j.issn.1006-2475.2015.11.005

Abstract

Abstract:

There are two research directions on it, one is discourse partition, and the other is fuzzy relations. Firstly, aiming at the problem of fuzzy time series model of multi-scale ratio existing in the theory of discourse partition method, the paper puts forward a method that uses relative error of the geometric average adjacent data instead of the arithmetic mean, in order to improve the precision of fuzzy intervals and the accuracy of prediction. Secondly, if the periodic time sequence using observations of continuous time to represent the fuzzy logic relation will exist a lot of prediction error, the paper comes up with using cycle as the interval of time series observation value indicates the fuzzy logic relationship. This method not only simplifies the fuzzy relationship matrix, but also reduces the algorithm complexity. Finally, the effectiveness of this method through Chongqing Net Bars traffic forecast is demonstrated in the paper.
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Key words: fuzzy time series model, multi-scale ratio, geometric average, periodic time series

CLC Number:

TP273

WANG Yang1,2, CHEN Hai-yan1,2, PENG Yan-bing1,2. Research on Discourse Partition of Fuzzy Time Series Models[J]. Computer and Modernization, doi: 10.3969/j.issn.1006-2475.2015.11.005.

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