| Presentation | 2021-12-16 Multivariate time series forecasting accuracy improvement method based on LSTNet Hayato Sano, Jun Rokui, |
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| PDF Download Page |  PDF download Page Link |
| Abstract(in Japanese) | (See Japanese page) |
| Abstract(in English) | Multivariate time series forecasting is a field to predict future values by analyzing the past of multiple time series data, and various methods have been proposed.In this study, two techniques with improved Long and Short term Time series Network(LSTNet) are proposed. LSTNet has a problem that long-term forecasts cannot be made for data with large scale changes. Therefore, Multiple Autoregressive LSTNet (MALSTNet) is proposed as a model with plural autoregressive layers. In addition, Gated recurrent unit (GRUs) used in Recurrent layers refer to historical data uniformly. It is unlikely that all historical information has an impact on forecasting uniformly, and Attention-LSTNet(ALSTNet) is proposed as a model that emphasizes certain historical interval information. In this study, we verified the effectiveness of the two methods from verification experiments. |
| Keyword(in Japanese) | (See Japanese page) |
| Keyword(in English) | Multivariate Time Series Forecasting / Autoregressive / Long and Short term Time series Network / LSTNet |
| Paper # | PRMU2021-37 |
| Date of Issue | 2021-12-09 (PRMU) |
| Conference Information | |
| Committee | PRMU |
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| Conference Date | 2021/12/16(2days) |
| Place (in Japanese) | (See Japanese page) |
| Place (in English) | Online |
| Topics (in Japanese) | (See Japanese page) |
| Topics (in English) | |
| Chair | Seiichi Uchida(Kyushu Univ.) |
| Vice Chair | Masakazu Iwamura(Osaka Pref. Univ.) / Mitsuru Anpai(Denso IT Lab.) |
| Secretary | Masakazu Iwamura(NTT) / Mitsuru Anpai(Tottori Univ.) |
| Assistant | Kouta Yamaguchi(CyberAgent) / Yusuke Matsui(Univ. of Tokyo) |
| Paper Information | |
| Registration To | Technical Committee on Pattern Recognition and Media Understanding |
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| Language | JPN |
| Title (in Japanese) | (See Japanese page) |
| Sub Title (in Japanese) | (See Japanese page) |
| Title (in English) | Multivariate time series forecasting accuracy improvement method based on LSTNet |
| Sub Title (in English) | |
| Keyword(1) | Multivariate Time Series Forecasting |
| Keyword(2) | Autoregressive |
| Keyword(3) | Long and Short term Time series Network |
| Keyword(4) | LSTNet |
| 1st Author's Name | Hayato Sano |
| 1st Author's Affiliation | University of Shizuoka(Univ of Shizuoka) |
| 2nd Author's Name | Jun Rokui |
| 2nd Author's Affiliation | University of Shizuoka(Univ of Shizuoka) |
| Date | 2021-12-16 |
| Paper # | PRMU2021-37 |
| Volume (vol) | vol.121 |
| Number (no) | PRMU-304 |
| Page | pp.pp.71-76(PRMU), |
| #Pages | 6 |
| Date of Issue | 2021-12-09 (PRMU) |