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


Project Open Call 3rd-party funding

TARGET-X


Duration:

GA Number: 101096614

SNS JU Call (Stream):
Call 1
Stream D

This tool has received funding from the European Union’s Horizon Europe Research and Innovation programme under the SNS ICE project (Grant Agreement No 101095841)