ST-CRMF: Compensated Residual Matrix Factorization with Spatial-Temporal Regularization for Graph-Based Time Series Forecasting
Despite the extensive efforts, accurate traffic time series forecasting remains challenging. By taking into account the non-linear nature of traffic in-depth, we propose a novel ST-CRMF model consisting of the Compensated Residual Matrix Factorization with Spatial-Temporal regularization for graph-b...
Main Authors: | , , , , , , |
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Format: | Article |
Language: | English |
Published: |
MDPI AG
2022-08-01
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Series: | Sensors |
Subjects: | |
Online Access: | https://www.mdpi.com/1424-8220/22/15/5877 |