Abstract
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.
| Original language | English |
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| Title of host publication | IEEE International Conference on Fuzzy Systems |
| Place of Publication | Piscataway, NJ, United States |
| Publisher | IEEE |
| Pages | 1127-1132 |
| Number of pages | 6 |
| Volume | 2 |
| Publication status | Published - 1997 |
| Externally published | Yes |
| Event | Proceedings of the 1997 6th IEEE International Conference on Fussy Systems, FUZZ-IEEE'97. Part 1 (of 3) - Barcelona, Spain Duration: 1997 Jul 1 → 1997 Jul 5 |
Other
| Other | Proceedings of the 1997 6th IEEE International Conference on Fussy Systems, FUZZ-IEEE'97. Part 1 (of 3) |
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| City | Barcelona, Spain |
| Period | 97/7/1 → 97/7/5 |
ASJC Scopus subject areas
- Chemical Health and Safety
- Software
- Safety, Risk, Reliability and Quality