Forecasting mid-long term electric energy consumption through bagging ARIMA and exponential smoothing methods

By Erick Meira Oliveira, F. C. Oliveira. 2018

377 citations recorded by the source corpus.

Subfields: Electrical and Electronic Engineering, Management Science and Operations Research

View Paper: https://www.semanticscholar.org/paper/187299a53ed177d2ac7e52031c36eb4233a4983d

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

1. Mariam Elnour
2. Yassine Himeur
3. F. Fadli
4. Nader Meskin
5. I. Petri
6. Yacine Rezgui
7. Faycal Bensaali
8. Abbes Amira

Citations in the corpus

• AI-big data analytics for building automation and management systems: a survey, actual challenges and future perspectives (2022, methodology): “For instance, bagging ARIMA (BARIMA) in de Oliveira and Oliveira (2018) is proposed to conduct a mid-long term load forecasting, while in Khwaja et al.”