A new defuzzifying process of type-2 fuzzy data modeling
In modeling uncertainty complex data that consisted of uncertainty in uncertainty data problem need specific theory to define the data problem. The specific theory to overcome this problem is the type2 fuzzy theory or type-2 fuzzy number since it deals with numbers. In order to obtain a crisp fuzzy...
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| 格式: | Proceedings |
| 語言: | English English |
| 出版: |
Faculty of Science and Natural Resources
2020
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| 在線閱讀: | https://eprints.ums.edu.my/id/eprint/21445/1/A%20new%20defuzzifying%20process%20of%20type-2%20fuzzy%20data%20modeling.pdf https://eprints.ums.edu.my/id/eprint/21445/2/A%20new%20defuzzifying%20process%20of%20type-2%20fuzzy%20data%20modeling1.pdf https://eprints.ums.edu.my/id/eprint/21445/ https://www.ums.edu.my/fssa/wp-content/uploads/2020/12/PROCEEDINGS-BOOK-ST-2020-e-ISSN.pdf |
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| 總結: | In modeling uncertainty complex data that consisted of uncertainty in uncertainty data problem need specific theory to define the data problem. The specific theory to overcome this problem is the type2 fuzzy theory or type-2 fuzzy number since it deals with numbers. In order to obtain a crisp fuzzy solution, the processes such as fuzzifying, fuzzification, type-reduction and defuzzification are needed. But in this paper, the new defuzzification process will be proposed which can be used to reduce the calculation or execution time. Therefore, this new defuzzification process will give the crisp fuzzy result in which the type-reduction process is excluded from this processing. A numerical example will be given to give more comprehension of the existing and proposed methods. |
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