Fuzzy (and Interval) techniques in the age of big data: An overview with applications to environmental science, geosciences, engineering, and medicine
© 2015 World Scientific Publishing Company. In some practical situations - e.g., when treating a new illness - we do not have enough data to make valid statistical conclusions. In such situations, it is necessary to use expert knowledge - and thus, it is beneficial to use fuzzy techniques that were...
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| Main Authors: | , |
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| Format: | Journal |
| Published: |
2018
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| Subjects: | |
| Online Access: | https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=84954042264&origin=inward http://cmuir.cmu.ac.th/jspui/handle/6653943832/44018 |
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| Institution: | Chiang Mai University |
| Summary: | © 2015 World Scientific Publishing Company. In some practical situations - e.g., when treating a new illness - we do not have enough data to make valid statistical conclusions. In such situations, it is necessary to use expert knowledge - and thus, it is beneficial to use fuzzy techniques that were specifically designed to process such knowledge. At first glance, it may seem that in situations when we have large amounts of data, the relative importance of expert knowledge should decrease. However, somewhat surprisingly, it turns out that expert knowledge is still very useful in the current age of big data. In this paper, we explain how exactly (and why) expert knowledge is useful, and we overview efficient methods for processing this knowledge. This overview is illustrated by examples from environmental science, geosciences, engineering (in particular, aircraft maintenance and underwater robots), and medicine. |
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