An Online Multistep-Forward Voltage-Prediction Approach Based on an LSTM-TD Model and KF Algorithm.
We propose a multistep-forward voltage-prediction approach combining a long short-term memory time-distributed model and the Kalman filter algorithm to improve prediction efficiency and reduce the demand for computing capability.
| Publicado en: | Computer (00189162) Vol. 54; no. 8; pp. 56 - 66 |
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| Autores principales: | , , , , |
| Formato: | Artículo |
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IEEE
Aug2021
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| Materias: | |
| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=hlh&AN=153128298&site=ehost-live header: @attributes: shortDbName: hlh uiTerm: 153128298 longDbName: Humanities International Complete uiTag: AN controlInfo: bkinfo: jinfo: jid: 00189162 PUT jtl: Computer (00189162) issn: 00189162 maglogo: N pubinfo: dt: Aug2021 vid: 54 iid: 8 pid: 13605 pub: IEEE artinfo: ui: 153128298 10.1109/MC.2021.3070314 ppf: 56 ppct: 10 formats: tig: atl: An Online Multistep-Forward Voltage-Prediction Approach Based on an LSTM-TD Model and KF Algorithm. aug: au: Ni, Ye Xia, Zhilong Zhao, Fangtong Fang, Chunrong Chen, Zhenyu affil: State Key Laboratory for Novel Software Technology, Nanjing University, Nanjing, Jiangsu, China University of Akron, Akron, Ohio United States State Key Laboratory for Novel Software Technology, Nanjing University, Nanjing, 210093 Jiangsu, China State Key Laboratory for Novel Software Technology, Nanjing University, Jiangsu, 210093 Jiangsu, China su: Demand forecasting Kalman filtering Algorithms On-demand computing Prediction models sug: subj: Demand forecasting Kalman filtering Algorithms On-demand computing Prediction models keyword: Computational modeling Kalman filters Memory management Prediction algorithms Predictive models ab: We propose a multistep-forward voltage-prediction approach combining a long short-term memory time-distributed model and the Kalman filter algorithm to improve prediction efficiency and reduce the demand for computing capability. pubtype: Academic Journal doctype: Article src: R language: English refInfo: copyright: @attributes: flag: Y dt: @attributes: year: 2021 holdings: @attributes: islocal: N |
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