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このアイテムの引用には次の識別子を使用してください:
http://hdl.handle.net/10119/3830
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| タイトル: | Merging fuzzy statistical data with imprecise prior information - application in solving complex decision problems |
| 著者: | Olgierd, Hryniewicz |
| キーワード: | Bayes decision-making
imprecise information
fuzzy statistical data
possibilistic decisions |
| 発行日: | Nov-2005 |
| 出版者: | JAIST Press |
| 抄録: | Solving complex decision problems requires the usage of information from different sources. Usually this information is uncertain and statistical or probabilistic methods are needed for its processing. However, in many cases a decision maker faces not only uncertainty of a random nature but also imprecision in the description of input data that is rather of linguistic nature. Therefore, there is a need to merge uncertainties of both types into one mathematical model. In the paper we present methodology of merging information from imprecisely reported statistical data and imprecisely formulated fuzzy prior information. Moreover, we also consider the case of imprecisely defined loss functions. The proposed methodology may be considered as the application of fuzzy statistical methods for the decision making in the systems analysis. |
| 記述: | The original publication is available at JAIST Press http://www.jaist.ac.jp/library/jaist-press/index.html
IFSR 2005 : Proceedings of the First World Congress of the International Federation for Systems Research : The New Roles of Systems Sciences For a Knowledge-based Society : Nov. 14-17, 2040, Kobe, Japan
Symposium 4, Session 2 : Meta-synthesis and Complex Systems Complex Problem Solving (I) |
| 言語: | ENG |
| URI: | http://hdl.handle.net/10119/3830 |
| ISBN: | 4-903092-02-X |
| 出現コレクション: | IFSR 2005
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このアイテムのファイル:
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記述 |
サイズ | 形式 |
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| 20076.pdf | | 99Kb | Adobe PDF | 見る/開く |
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