Fuzzy Principal Component Analysis for Fuzzy Data
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概要
- 論文の詳細を見る
In this paper, a fuzzy concept is employed to construct a principal component model which can deal with fuzziness, vagueness or possibility, which is named a fuzzy principal component analysis for fuzzy data. The fuzzy principal component analysis is to analyze a 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 about 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 indices. And we evaluate the possibility of a company activity in information technology industry.
- バイオメディカル・ファジィ・システム学会の論文
- 1997-10-16
著者
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Watada Junzo
Department Of Industrial Management Osaka Institute Of Technology
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Nakamori Yoshiteru
Department Of Applied Mathematics Konan University
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YABUUCHI Yoshiyuki
Department of Industrial Management, Osaka Institute of Technology
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Yabuuchi Yoshiyuki
Department Of Industrial Management Osaka Institute Of Technology
関連論文
- Fuzzy Principal Component Analysis and Its Application
- Fuzzy Principal Component Analysis for Fuzzy Data
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