Heterogeneous data fusion considering spatial correlations using graph convolutional networks and its application in air quality prediction
Models that predict the future state of certain observations are commonly developed by utilizing heterogeneous data. Most traditional prediction models tend to ignore inconsistencies and imperfections in heterogeneous data, and they are also limited in their ability to consider spatial correlations...
| Main Authors: | , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
King Saud bin Abdulaziz University
2022
|
| Subjects: | |
| Online Access: | View Fulltext in Publisher |