Interval estimation of forecasting value by using trapezoidal fuzzy number
One of the major highlights of the fuzzy time series forecasting model is that it only provides one single point forecasted value, as in the traditional time series methods. One of the major highlights of the fuzzy time series forecasting model is that it only provides one single point forecasted va...
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| Main Authors: | , , |
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| Format: | Proceedings |
| Language: | English English |
| Published: |
Pusat e-pembelajaran, UMS
2022
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| Subjects: | |
| Online Access: | https://eprints.ums.edu.my/id/eprint/41234/1/ABSTRACT.pdf https://eprints.ums.edu.my/id/eprint/41234/2/FULL%20TEXT.pdf https://eprints.ums.edu.my/id/eprint/41234/ https://oer.ums.edu.my/handle/oer_source_files/2441 |
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| Institution: | Universiti Malaysia Sabah |
| Language: | English English |
| Summary: | One of the major highlights of the fuzzy time series forecasting model is that it only provides one single point forecasted value, as in the traditional time series methods. One of the major highlights of the fuzzy time series forecasting model is that it only provides one single point forecasted value, as in the traditional time series methods. Besides, most of the models use triangular fuzzy numbers in their methods. The aim of this paper is to show that the forecasted value will be a trapezoidal fuzzy number in interval form instead of a single-point value. In our case, we applied tuberculosis cases collected in Sabah to examine this method. Two numerical data sets from the whole tuberculosis data set were used to illustrate the chosen methods. |
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