Real-time data-processing framework with model updating for digital twins of water treatment facilities
Machine learning (ML) models are now widely used in digital twins of water treatment facilities. These models are commonly trained based on historical datasets, and their predictions serve various important objectives, such as anomaly detection and optimization. While predictions from the trained mo...
| Main Authors: | , , |
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| Other Authors: | |
| Format: | Journal Article |
| Language: | English |
| Published: |
2023
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| Subjects: | |
| Online Access: | https://hdl.handle.net/10356/165234 |