How to fully represent expert information about imprecise properties in a computer system: Random sets, fuzzy sets, and beyond: An overview
To help computers make better decisions, it is desirable to describe all our knowledge in computer-understandable terms. This is easy for knowledge described in terms on numerical values: we simply store the corresponding numbers in the computer. This is also easy for knowledge about precise (well-d...
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| Main Authors: | , |
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| 格式: | 雜誌 |
| 出版: |
2018
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| 主題: | |
| 在線閱讀: | https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=84899441488&origin=inward http://cmuir.cmu.ac.th/jspui/handle/6653943832/53370 |
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| 機構: | Chiang Mai University |
| 總結: | To help computers make better decisions, it is desirable to describe all our knowledge in computer-understandable terms. This is easy for knowledge described in terms on numerical values: we simply store the corresponding numbers in the computer. This is also easy for knowledge about precise (well-defined) properties which are either true or false for each object: we simply store the corresponding "true" and "false" values in the computer. The challenge is how to store information about imprecise properties. In this paper, we overview different ways to fully store the expert information about imprecise properties. We show that in the simplest case, when the only source of imprecision is disagreement between different experts, a natural way to store all the expert information is to use random sets; we also show how fuzzy sets naturally appear in such random set representation. We then show how the random set representation can be extended to the general ("fuzzy") case when, in addition to disagreements, experts are also unsure whether some objects satisfy certain properties or not. © 2014 Taylor and Francis. |
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