抄録
The characteristic of the fuzzy regression model is to enwrap all the given samples. An interval of fuzzy regression model is created by considering how far a sample is from the central values. That means when samples are widely scattered the size of an interval of the fuzzy model is widened. That is, the fuzziness of the fuzzy regression model is decided by the range of sample distribution. Therefore, many research results on a fuzzy regression model in order to describe the possibility of the target system have been reported. We have proposed two fuzzy robust regression models which remove influences of improper data such as unusual data and outliers. In this paper, we describe the model building of our fuzzy robust regressions by removing influences of improper data.
| 本文言語 | English |
|---|---|
| ホスト出版物のタイトル | 2014 Joint 7th International Conference on Soft Computing and Intelligent Systems, SCIS 2014 and 15th International Symposium on Advanced Intelligent Systems, ISIS 2014 |
| 出版社 | Institute of Electrical and Electronics Engineers Inc. |
| ページ | 1386-1391 |
| ページ数 | 6 |
| ISBN（印刷版） | 9781479959556 |
| DOI | |
| 出版ステータス | Published - 2014 2月 18 |
| イベント | 2014 Joint 7th International Conference on Soft Computing and Intelligent Systems, SCIS 2014 and 15th International Symposium on Advanced Intelligent Systems, ISIS 2014 - Kitakyushu, Japan 継続期間: 2014 12月 3 → 2014 12月 6 |
Other
| Other | 2014 Joint 7th International Conference on Soft Computing and Intelligent Systems, SCIS 2014 and 15th International Symposium on Advanced Intelligent Systems, ISIS 2014 |
|---|---|
| 国/地域 | Japan |
| City | Kitakyushu |
| Period | 14/12/3 → 14/12/6 |
ASJC Scopus subject areas
- ソフトウェア
- 人工知能