Ensemble forecasting method published in JIIS journal

3/20/2019 Big data

The Journal of Intelligent Information Systems (JIIS), which is published by Springer and listed in Current Contents database, issued a paper by the team of researchers from the Faculty of Informatics and Information Technologies, Slovak University of Technology in Bratislava titled

Density-based unsupervised ensemble learning methods for time series forecasting of aggregated or clustered electricity consumption.

The research focused on ensemble power load forecasting from smart metering data of a group of consumers. To form the groups of consumers clustering methods were employed. The work was partially supported by the ITMS 26240120039 project.

Laurinec, P., Lóderer, M., Lucká, M., & Rozinajová, V. (2019). Density-based unsupervised ensemble learning methods for time series forecasting of aggregated or clustered electricity consumption. Journal of Intelligent Information Systems, 1–21. https://doi.org/10.1007/s10844-019-00550-3