State of the Art Machine Learning Techniques for Time Series Forecasting: A Survey
Time Series Forecasting is vital for wide range of domains such as financial market forecasting, earthquake forecasting, weather forecasting, electric power demand forecasting and etc. The past 25 years of time series forecasting research that has been reviewed in (Tinbergen Institute Discussion Pap...
| Main Authors: | , |
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| Format: | Proceeding Paper |
| Language: | English |
| Published: |
2015
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| Subjects: | |
| Online Access: | http://irep.iium.edu.my/48055/ http://irep.iium.edu.my/48055/1/ID_122.pdf |
| _version_ | 1848783241720365056 |
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| author | Nyein Naing, Wai Yan Htike@Muhammad Yusof, Zaw Zaw |
| author_facet | Nyein Naing, Wai Yan Htike@Muhammad Yusof, Zaw Zaw |
| author_sort | Nyein Naing, Wai Yan |
| building | IIUM Repository |
| collection | Online Access |
| description | Time Series Forecasting is vital for wide range of domains such as financial market forecasting, earthquake forecasting, weather forecasting, electric power demand forecasting and etc. The past 25 years of time series forecasting research that has been reviewed in (Tinbergen Institute Discussion Paper: International Journal of Forecasting) for the period of 1985 to 2005. Therefore, the purpose of my paper is continue to review the recent 10 years of different state of the machine learning techniques for time series forecasting . The main contribution of this paper is to supply researchers with a cohesive overview of state of the art machine learning techniques (during the period of 2005 to 2015) and to identify possible opportunities for future research. |
| first_indexed | 2025-11-14T16:18:14Z |
| format | Proceeding Paper |
| id | iium-48055 |
| institution | International Islamic University Malaysia |
| institution_category | Local University |
| language | English |
| last_indexed | 2025-11-14T16:18:14Z |
| publishDate | 2015 |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | iium-480552018-06-26T02:59:40Z http://irep.iium.edu.my/48055/ State of the Art Machine Learning Techniques for Time Series Forecasting: A Survey Nyein Naing, Wai Yan Htike@Muhammad Yusof, Zaw Zaw T Technology (General) Time Series Forecasting is vital for wide range of domains such as financial market forecasting, earthquake forecasting, weather forecasting, electric power demand forecasting and etc. The past 25 years of time series forecasting research that has been reviewed in (Tinbergen Institute Discussion Paper: International Journal of Forecasting) for the period of 1985 to 2005. Therefore, the purpose of my paper is continue to review the recent 10 years of different state of the machine learning techniques for time series forecasting . The main contribution of this paper is to supply researchers with a cohesive overview of state of the art machine learning techniques (during the period of 2005 to 2015) and to identify possible opportunities for future research. 2015 Proceeding Paper PeerReviewed application/pdf en http://irep.iium.edu.my/48055/1/ID_122.pdf Nyein Naing, Wai Yan and Htike@Muhammad Yusof, Zaw Zaw (2015) State of the Art Machine Learning Techniques for Time Series Forecasting: A Survey. In: International Conference on Advances Technology in Telecommunication, Broadcasting, and Satellite, 26-27 September, 2015, Jakarta, Indonesia. (In Press) http://telsatech.org/ |
| spellingShingle | T Technology (General) Nyein Naing, Wai Yan Htike@Muhammad Yusof, Zaw Zaw State of the Art Machine Learning Techniques for Time Series Forecasting: A Survey |
| title | State of the Art Machine Learning Techniques for Time Series Forecasting: A Survey |
| title_full | State of the Art Machine Learning Techniques for Time Series Forecasting: A Survey |
| title_fullStr | State of the Art Machine Learning Techniques for Time Series Forecasting: A Survey |
| title_full_unstemmed | State of the Art Machine Learning Techniques for Time Series Forecasting: A Survey |
| title_short | State of the Art Machine Learning Techniques for Time Series Forecasting: A Survey |
| title_sort | state of the art machine learning techniques for time series forecasting: a survey |
| topic | T Technology (General) |
| url | http://irep.iium.edu.my/48055/ http://irep.iium.edu.my/48055/ http://irep.iium.edu.my/48055/1/ID_122.pdf |