Multivariate time series forecasting via attention-based encoder–decoder framework

Time series forecasting is an important technique to study the behavior of temporal data and forecast future values, which is widely applied in many fields, e.g. air quality forecasting, power load forecasting, medical monitoring, and intrusion detection. In this paper, we firstly propose a novel te...

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Vydané v:	Neurocomputing (Amsterdam) Ročník 388; s. 269 - 279
Hlavní autori:	Du, Shengdong, Li, Tianrui, Yang, Yan, Horng, Shi-Jinn
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Elsevier B.V 07.05.2020
Predmet:	Deep learning Encoder–decoder Long short-term memory networks Multi-step forecasting Multivariate time series Temporal attention Temporal attention Encoder–decoder Deep learning Multivariate time series Long short-term memory networks Multi-step forecasting
ISSN:	0925-2312, 1872-8286
On-line prístup:	Získať plný text
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