Prediction Method of Multiple Related Time Series Based on Generative Adversarial Networks

Prediction Method of Multiple Related Time Series Based on Generative Adversarial Networks

In multiple related time series prediction problems, the key is capturing the comprehensive influence of the temporal dependencies within each time series and the interactional dependencies between time series. At present, most time series prediction methods are difficult to capture the complex inte...

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Bibliographic Details
Main Authors:	Weijie Wu, Fang Huang, Yidi Kao, Zhou Chen, Qi Wu
Format:	Article
Language:	English
Published:	MDPI AG 2021-01-01
Series:	Information
Subjects:	multiple related time series prediction interactional dependencies generation generative adversarial networks graph convolutional networks long short-term memory networks
Online Access:	https://www.mdpi.com/2078-2489/12/2/55

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