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https://doi.org/10.1109/fuzzy....
Article . 2002 . Peer-reviewed
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Fuzzy principal component analysis for fuzzy data

Authors: WATADA, Junzo; YABUUCHI, Yoshiyuki; NAKAMORI, Yoshiteru;

Fuzzy principal component analysis for fuzzy data

Abstract

A fuzzy concept is employed to construct a principal component model which can deal with fuzziness, vagueness or possibility, which is called fuzzy principal component analysis for fuzzy data. The fuzzy principal component analysis analyzes the possibility of fuzzy data. The fuzzy principal component analysis for fuzzy data has three formulations according the portions which the possibilities included in fuzzy data are embodied: (1) an eigenvalue, (2) an eigenvector and (3) both eigenvalue and eigenvector. In this paper, we discuss only the first formulation that an eigenvalue is employed to deal with fuzziness of data. The principal component analysis for fuzzy data is employed in this paper to analyze the features of information technology industry. In this analysis, the financial ratio is employed as an index. We evaluate the possibility of a company activity in the information technology industry.

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    popularity
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    influence
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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!
8
Average
Top 10%
Average