TARGET-X
5GEdge_ForecastOptimiser
5GEdge_ForecastOptimiser leverages the capabilities of Deep Neural Networks and implements a methodology that dynamically chooses the optimal forecasting algorithm for each consumption pattern. The benefit is that 5GEdge_ForecastOptimiser provides a better pattern-to-algorithm fit and thus achieves better forecasting accuracy without the involvement of the end-user, because 5GEdge_ForecastOptimiser dynamically chooses the best algorithms to fit the given pattern for which the prediction is sought by the end user.
Type of experiment:
Trial
Functionality:
Ultra-Reliable and Low Latency Communications (URLLC)
Maturity:
Location(s):
Germany
Vertical sector(s):
Smart Energy
Smart Energy
Project Open Call 3rd-party funding
TARGET-X
Duration:
GA Number:
101096614
SNS JU Call (Stream):
Call 1
Stream D

