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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Bibliographic Details

Published in:	Neurocomputing (Amsterdam) Vol. 388; pp. 269 - 279
Main Authors:	Du, Shengdong, Li, Tianrui, Yang, Yan, Horng, Shi-Jinn
Format:	Journal Article
Language:	English
Published:	Elsevier B.V 07.05.2020
Subjects:	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
Online Access:	Get full text
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