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| Title | New statistical approaches for fuzzy data |
| Creator | Wu, Berlin 吳柏林 Sun, C.-M. |
| Contributor | 應數系 |
| Key Words | Computational methods; Measurement errors; Random processes; Statistical methods; Uncertainty analysis; Fuzzy Kruskal Wallis tests; Fuzzy mean; Fuzzy median; Fuzzy modes; Fuzzy sampling survey; Fuzzy sets |
| Date | 2007 |
| Date Issued | 13-Jul-2015 15:35:56 (UTC+8) |
| Summary | Real observations of qualities (continuous or discrete types) are not precise numbers but more or less non-precise. The best description of such data is by so-called fuzzy numbers. The fuzziness is different from measurement errors and stochastic uncertainty. In this paper we propose definitions of fuzzy mode, fuzzy median and fuzzy mean as well as investigation of their related properties and employ these techniques in the practical applications of real life. Empirical result shows that fuzzy statistics with soft computing is more realistic and reasonable for the statistical research. Finally certain comments are suggested for the further studies. We hope that this reformation will make the corresponding fuzzy techniques more appropriate and efficient to researchers whose only experience with statistics is using the traditional methods. © World Scientific Publishing Company. |
| Relation | International Journal of Uncertainty, Fuzziness and Knowlege-Based Systems,Volume 15, SUPPL. 2, Pages 89-106 |
| Type | article |
| DOI | http://dx.doi.org/10.1142/S0218488507004637 |
| dc.contributor | 應數系 | - |
| dc.creator (作者) | Wu, Berlin | - |
| dc.creator (作者) | 吳柏林 | - |
| dc.creator (作者) | Sun, C.-M. | en_US |
| dc.date (日期) | 2007 | - |
| dc.date.accessioned | 13-Jul-2015 15:35:56 (UTC+8) | - |
| dc.date.available | 13-Jul-2015 15:35:56 (UTC+8) | - |
| dc.date.issued (上傳時間) | 13-Jul-2015 15:35:56 (UTC+8) | - |
| dc.identifier.uri (URI) | http://nccur.lib.nccu.edu.tw/handle/140.119/76503 | - |
| dc.description.abstract (摘要) | Real observations of qualities (continuous or discrete types) are not precise numbers but more or less non-precise. The best description of such data is by so-called fuzzy numbers. The fuzziness is different from measurement errors and stochastic uncertainty. In this paper we propose definitions of fuzzy mode, fuzzy median and fuzzy mean as well as investigation of their related properties and employ these techniques in the practical applications of real life. Empirical result shows that fuzzy statistics with soft computing is more realistic and reasonable for the statistical research. Finally certain comments are suggested for the further studies. We hope that this reformation will make the corresponding fuzzy techniques more appropriate and efficient to researchers whose only experience with statistics is using the traditional methods. © World Scientific Publishing Company. | - |
| dc.format.extent | 176 bytes | - |
| dc.format.mimetype | text/html | - |
| dc.relation (關聯) | International Journal of Uncertainty, Fuzziness and Knowlege-Based Systems,Volume 15, SUPPL. 2, Pages 89-106 | - |
| dc.subject (關鍵詞) | Computational methods; Measurement errors; Random processes; Statistical methods; Uncertainty analysis; Fuzzy Kruskal Wallis tests; Fuzzy mean; Fuzzy median; Fuzzy modes; Fuzzy sampling survey; Fuzzy sets | - |
| dc.title (題名) | New statistical approaches for fuzzy data | - |
| dc.type (資料類型) | article | en |
| dc.identifier.doi (DOI) | 10.1142/S0218488507004637 | - |
| dc.doi.uri (DOI) | http://dx.doi.org/10.1142/S0218488507004637 | - |