A simulation study of first-order autoregressive to evaluate the performance of measurement error based symmetry triangular fuzzy number
Data collected by various data collection methods are often exposed to uncertainties that may affect the information presented by quantitative results. This also causes the forecasted model developed to be less precise because of the uncertainty contained in the input data used. Hence, preparing the...
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| Format: | Article |
| Language: | en |
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Institute of Advanced Engineering and Science IAES
2020
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| Online Access: | http://eprints.uthm.edu.my/5295/1/AJ%202020%20%28140%29.pdf http://eprints.uthm.edu.my/5295/ https://dx.doi.org/10.11591/ijeecs.v18.i3.pp1559-1567 |
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| _version_ | 1833417819482488832 |
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| author | Che Lah, Muhammad Shukri Arbaiy, Nureize |
| author_facet | Che Lah, Muhammad Shukri Arbaiy, Nureize |
| author_sort | Che Lah, Muhammad Shukri |
| building | UTHM Library |
| collection | Institutional Repository |
| content_provider | Universiti Tun Hussein Onn Malaysia |
| content_source | UTHM Institutional Repository |
| continent | Asia |
| country | Malaysia |
| description | Data collected by various data collection methods are often exposed to uncertainties that may affect the information presented by quantitative results. This also causes the forecasted model developed to be less precise because of the uncertainty contained in the input data used. Hence, preparing the data by means of handling inherent uncertainties is necessary to avoid the developed forecasting model to be less accurate. Traditional autoregressive (AR) model uses precise values and deals with the uncertainty normally in forecasting model. Fewer researches are focused on data preparation in time-series autoregressive for handling the uncertainties in data. Hence, this paper proposes a procedure to perform data preparation to handle uncertainty. The fuzzy data preparation involves the construction of fuzzy symmetric triangle numbers using percentage error and standard deviation method. The proposed approach is evaluated by using the simulation method for first-order autoregressive, AR (1) model in terms of forecasting accuracy performance. Simulation result demonstrates that the proposed approach obtains smaller error in forecasting and hence achieving better forecasting accuracy and dealing with uncertainty in the analysis. |
| format | Article |
| id | my.uthm.eprints-5295 |
| institution | Universiti Tun Hussein Onn Malaysia |
| language | en |
| publishDate | 2020 |
| publisher | Institute of Advanced Engineering and Science IAES |
| record_format | eprints |
| spelling | my.uthm.eprints-52952022-01-09T02:43:02Z http://eprints.uthm.edu.my/5295/ A simulation study of first-order autoregressive to evaluate the performance of measurement error based symmetry triangular fuzzy number Che Lah, Muhammad Shukri Arbaiy, Nureize T Technology (General) QA71-90 Instruments and machines Data collected by various data collection methods are often exposed to uncertainties that may affect the information presented by quantitative results. This also causes the forecasted model developed to be less precise because of the uncertainty contained in the input data used. Hence, preparing the data by means of handling inherent uncertainties is necessary to avoid the developed forecasting model to be less accurate. Traditional autoregressive (AR) model uses precise values and deals with the uncertainty normally in forecasting model. Fewer researches are focused on data preparation in time-series autoregressive for handling the uncertainties in data. Hence, this paper proposes a procedure to perform data preparation to handle uncertainty. The fuzzy data preparation involves the construction of fuzzy symmetric triangle numbers using percentage error and standard deviation method. The proposed approach is evaluated by using the simulation method for first-order autoregressive, AR (1) model in terms of forecasting accuracy performance. Simulation result demonstrates that the proposed approach obtains smaller error in forecasting and hence achieving better forecasting accuracy and dealing with uncertainty in the analysis. Institute of Advanced Engineering and Science IAES 2020 Article PeerReviewed text en http://eprints.uthm.edu.my/5295/1/AJ%202020%20%28140%29.pdf Che Lah, Muhammad Shukri and Arbaiy, Nureize (2020) A simulation study of first-order autoregressive to evaluate the performance of measurement error based symmetry triangular fuzzy number. Indonesian Journal of Electrical Engineering and Computer Science, 18 (3). pp. 1559-1567. ISSN 2502-4752 https://dx.doi.org/10.11591/ijeecs.v18.i3.pp1559-1567 |
| spellingShingle | T Technology (General) QA71-90 Instruments and machines Che Lah, Muhammad Shukri Arbaiy, Nureize A simulation study of first-order autoregressive to evaluate the performance of measurement error based symmetry triangular fuzzy number |
| title | A simulation study of first-order autoregressive to evaluate the performance of measurement error based symmetry triangular fuzzy number |
| title_full | A simulation study of first-order autoregressive to evaluate the performance of measurement error based symmetry triangular fuzzy number |
| title_fullStr | A simulation study of first-order autoregressive to evaluate the performance of measurement error based symmetry triangular fuzzy number |
| title_full_unstemmed | A simulation study of first-order autoregressive to evaluate the performance of measurement error based symmetry triangular fuzzy number |
| title_short | A simulation study of first-order autoregressive to evaluate the performance of measurement error based symmetry triangular fuzzy number |
| title_sort | simulation study of first-order autoregressive to evaluate the performance of measurement error based symmetry triangular fuzzy number |
| topic | T Technology (General) QA71-90 Instruments and machines |
| url | http://eprints.uthm.edu.my/5295/1/AJ%202020%20%28140%29.pdf http://eprints.uthm.edu.my/5295/ https://dx.doi.org/10.11591/ijeecs.v18.i3.pp1559-1567 |
| url_provider | http://eprints.uthm.edu.my/ |