WEKO3
アイテム
Time series prediction using a hybrid model of neural network and FIR filter
http://hdl.handle.net/2297/6783
http://hdl.handle.net/2297/67831922b8b1-6436-46c4-a859-9adc2f88a632
| 名前 / ファイル | ライセンス | アクション |
|---|---|---|
TE-PR-NAKAYAMA-K-1975.pdf (348.5 kB)
|
|
| Item type | 会議発表論文 / Conference Paper(1) | |||||
|---|---|---|---|---|---|---|
| 公開日 | 2017-10-03 | |||||
| タイトル | ||||||
| タイトル | Time series prediction using a hybrid model of neural network and FIR filter | |||||
| 言語 | ||||||
| 言語 | eng | |||||
| 資源タイプ | ||||||
| 資源タイプ識別子 | http://purl.org/coar/resource_type/c_5794 | |||||
| 資源タイプ | conference paper | |||||
| 著者 |
Khalaf, Ashraf A.M.
× Khalaf, Ashraf A.M.× Nakayama, Kenji |
|||||
| 書誌情報 |
IEEE International Conference on Neural Networks - Conference Proceedings 巻 3, p. 1975-1980, 発行日 1998-05-01 |
|||||
| ISSN | ||||||
| 収録物識別子タイプ | ISSN | |||||
| 収録物識別子 | 1098-7576 | |||||
| 出版者 | ||||||
| 出版者 | IEEE(Institute of Electrical and Electronics Engineers) | |||||
| 抄録 | ||||||
| 内容記述タイプ | Abstract | |||||
| 内容記述 | Time series prediction is a very important technology in a wide variety of field. The actual time series contains both linear and nonlinear properties. The amplitude of the time series to be predicted is usually continuous value. For this reason, we combine nonlinear and linear predictors in a cascade form. In order to estimate the minimum size of the proposed predictor, we propose a nonlinearity analysis for the time series of interest. Computer simulations using the sunspot data have demonstrated the efficiency of the proposed predictor and the nonlinearity analysis. | |||||
| 著者版フラグ | ||||||
| 出版タイプ | VoR | |||||
| 出版タイプResource | http://purl.org/coar/version/c_970fb48d4fbd8a85 | |||||
