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Found 4 papers, 1 papers with code
Knowledge- and Data-driven Services for Energy Systems using Graph Neural Networks
The transition away from carbon-based energy sources poses several challenges for the operation of electricity distribution systems.
Scalable Deployment of AI Time-series Models for IoT
A knowledge-based approach to managing model and time-series data allows the use of general semantic concepts for expressing feature engineering tasks.
Castor: Contextual IoT Time Series Data and Model Management at Scale
The main features of Castor are: (1) an efficient pipeline for ingesting IoT time series data in real time; (2) a scalable, hybrid data management service for both time series and contextual data; (3) a versatile semantic model for contextual information which can be easily adopted to different application domains; (4) an abstract framework for developing and storing predictive models in R or Python; (5) deployment services which automatically train and/or score predictive models upon user-defined conditions.
Computation Other Statistics
Power Systems Data Fusion based on Belief Propagation
The increasing complexity of the power grid, due to higher penetration of distributed resources and the growing availability of interconnected, distributed metering devices re- quires novel tools for providing a unified and consistent view of the system.
