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Fuzzy Time Series Analysis and Forecasting

Authors: Wu, Berlin; Nguyen, H.T.;

Fuzzy Time Series Analysis and Forecasting

Abstract

The problem of system modeling and identification has attracted considerable attention during the past decades mostly because of a large number of applications in diverse fields. In this chapter we give a well defined fuzzy time series model with forecasting through the Markov fuzzy relation. An illustrative algorithm based on a fuzzy logic is developed to predicate the multivariate dynamic data. © Springer-Verlag Berlin Heidelberg 2006.

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Taiwan
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
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