Fuzzy principal component analysis for fuzzy data

Yoshiyuki Yabuuchi, Junzo Watada, Yoshiteru Nakamori

研究成果: Conference contribution

10 被引用数 (Scopus)

抄録

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 if 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.

本文言語English
ホスト出版物のタイトルIEEE International Conference on Fuzzy Systems
Place of PublicationPiscataway, NJ, United States
出版社IEEE
ページ1127-1132
ページ数6
2
出版ステータスPublished - 1997
外部発表はい
イベントProceedings of the 1997 6th IEEE International Conference on Fussy Systems, FUZZ-IEEE'97. Part 1 (of 3) - Barcelona, Spain
継続期間: 1997 7 11997 7 5

Other

OtherProceedings of the 1997 6th IEEE International Conference on Fussy Systems, FUZZ-IEEE'97. Part 1 (of 3)
CityBarcelona, Spain
Period97/7/197/7/5

ASJC Scopus subject areas

  • 化学的な安全衛生
  • ソフトウェア
  • 安全性、リスク、信頼性、品質管理

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