| dc.contributor | 應數系 | - |
| dc.creator (作者) | Wu, Berlin | - |
| dc.creator (作者) | 吳柏林 | zh_TW |
| dc.creator (作者) | Liu, Hsuan-Ku | en_US |
| dc.creator (作者) | Hsu, Yu-Yun | en_US |
| dc.date (日期) | 2010-03 | - |
| dc.date.accessioned | 1-Feb-2016 16:07:15 (UTC+8) | - |
| dc.date.available | 1-Feb-2016 16:07:15 (UTC+8) | - |
| dc.date.issued (上傳時間) | 1-Feb-2016 16:07:15 (UTC+8) | - |
| dc.identifier.uri (URI) | https://ah.lib.nccu.edu.tw/item?item_id=90441 | - |
| dc.description.abstract (摘要) | The goal of this paper is to construct a multiple fuzzy regression model by fuzzy parameters estimation using the fuzzy samples. We propose an optimization model that provides fuzzy coefficients to minimize the distance between the fuzzy regressands and the fuzzy regressors. It concerned with imprecise measurement of observed variables, linear programming estimation and non-parametric methods. This is different from the assumptions as well as the estimation techniques of the classical analysis. Empirical results demonstrate that our new approach is efficient and more realistic than the traditional regression analysis did. | - |
| dc.format.extent | 178038 bytes | - |
| dc.format.mimetype | application/pdf | - |
| dc.relation (關聯) | International Journal of Intelligent Technologies & Applied Statistics, 3(1), 45-55 | - |
| dc.subject (關鍵詞) | Fuzzy regression;Fuzzy parameter;H-cut;Methods of least square;Triangular membership function | - |
| dc.title (題名) | On the Optimization Methods for Fully Fuzzy Regression Models | - |
| dc.type (資料類型) | article | - |
