Application of Fuzzy Time Series Approach in Electric Load Forecasting
In electrical power management, load forecasting accuracy is an indispensable factor which influences the decision making and planning of power companies in the future. Previous research has explored various forecasting models to resolve this issue, ranging from linear and non-linear regression to a...
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| Format: | Article |
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World Scientific Publishing Co. Pte Ltd
2015
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| _version_ | 1796860393861152768 |
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| author | Ismail, Zuhaimy Efendi, Riswan Mat Deris, Mustafa |
| author_facet | Ismail, Zuhaimy Efendi, Riswan Mat Deris, Mustafa |
| author_sort | Ismail, Zuhaimy |
| collection | ePrints |
| description | In electrical power management, load forecasting accuracy is an indispensable factor which influences the decision making and planning of power companies in the future. Previous research has explored various forecasting models to resolve this issue, ranging from linear and non-linear regression to artificial intelligence algorithm. However, the absolute percentage error has yet to significantly improve using these models. Through this paper, the fuzzy time series (FTS) model was suggested to obtain better forecasted values and increases the forecasting accuracy. This accuracy could be obtained by using effective length of intervals of the discourse universe. The yearly dataset of Taiwan regional electric load was used for this empirical study and the reliability of the proposed model was compared with other previous models. The results indicated that the mean absolute percentage error (MAPE) of the proposed model (FTS) is smaller than MAPE obtained from those previous models. |
| first_indexed | 2024-03-05T19:40:42Z |
| format | Article |
| id | utm.eprints-57861 |
| institution | Universiti Teknologi Malaysia - ePrints |
| last_indexed | 2024-03-05T19:40:42Z |
| publishDate | 2015 |
| publisher | World Scientific Publishing Co. Pte Ltd |
| record_format | dspace |
| spelling | utm.eprints-578612021-07-28T14:49:16Z http://eprints.utm.my/57861/ Application of Fuzzy Time Series Approach in Electric Load Forecasting Ismail, Zuhaimy Efendi, Riswan Mat Deris, Mustafa QA Mathematics In electrical power management, load forecasting accuracy is an indispensable factor which influences the decision making and planning of power companies in the future. Previous research has explored various forecasting models to resolve this issue, ranging from linear and non-linear regression to artificial intelligence algorithm. However, the absolute percentage error has yet to significantly improve using these models. Through this paper, the fuzzy time series (FTS) model was suggested to obtain better forecasted values and increases the forecasting accuracy. This accuracy could be obtained by using effective length of intervals of the discourse universe. The yearly dataset of Taiwan regional electric load was used for this empirical study and the reliability of the proposed model was compared with other previous models. The results indicated that the mean absolute percentage error (MAPE) of the proposed model (FTS) is smaller than MAPE obtained from those previous models. World Scientific Publishing Co. Pte Ltd 2015 Article PeerReviewed Ismail, Zuhaimy and Efendi, Riswan and Mat Deris, Mustafa (2015) Application of Fuzzy Time Series Approach in Electric Load Forecasting. New Mathematics And Natural Computation, 11 (3). pp. 229-248. ISSN 1791-9320 DOI:10.1142/S1793005715500076 |
| spellingShingle | QA Mathematics Ismail, Zuhaimy Efendi, Riswan Mat Deris, Mustafa Application of Fuzzy Time Series Approach in Electric Load Forecasting |
| title | Application of Fuzzy Time Series Approach in Electric Load Forecasting |
| title_full | Application of Fuzzy Time Series Approach in Electric Load Forecasting |
| title_fullStr | Application of Fuzzy Time Series Approach in Electric Load Forecasting |
| title_full_unstemmed | Application of Fuzzy Time Series Approach in Electric Load Forecasting |
| title_short | Application of Fuzzy Time Series Approach in Electric Load Forecasting |
| title_sort | application of fuzzy time series approach in electric load forecasting |
| topic | QA Mathematics |
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