Abstract
Since a fuzzy linear regression model has been proposed in 1987, its possibilistic model is employed to analyze data. From view points of fuzzy linear regression, data are understood to express the possibilities of a latent system. When data have error or data are very irregular, the obtained regression model has unnaturally too wide possibility range. In this paper we propose a fuzzy robust linear regression which is not influenced by data with error. The model is built as rigid a model as possible to minimize the total error between the model and the data. The robustness of the proposed model is shown using numerical examples.
| 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 | 1370-1376 |
| Number of pages | 7 |
| Volume | 2 |
| Publication status | Published - 1994 |
| Externally published | Yes |
| Event | Proceedings of the 3rd IEEE Conference on Fuzzy Systems. Part 3 (of 3) - Orlando, FL, USA Duration: 1994 Jun 26 → 1994 Jun 29 |
Other
| Other | Proceedings of the 3rd IEEE Conference on Fuzzy Systems. Part 3 (of 3) |
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| City | Orlando, FL, USA |
| Period | 94/6/26 → 94/6/29 |
ASJC Scopus subject areas
- Chemical Health and Safety
- Software
- Safety, Risk, Reliability and Quality