Zobrazeno 1 - 3
of 3
pro vyhledávání: '"Huaikang Jin"'
Publikováno v:
Renewable Energy. 174:1-18
Ensemble learning models have been widely used for wind power forecasting to facilitate efficient dispatching of power systems. However, traditional ensemble methods cannot always function well due to insufficient accuracy and diversity of base learn
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::0d17aa922f72a4e2119c9084b10d7af3
https://doi.org/10.1016/j.renene.2021.04.028
https://doi.org/10.1016/j.renene.2021.04.028
Publikováno v:
2022 IEEE 11th Data Driven Control and Learning Systems Conference (DDCLS).
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::aba5884ea8b1140a52d7e0ed368c6d9c
https://doi.org/10.1109/ddcls55054.2022.9858579
https://doi.org/10.1109/ddcls55054.2022.9858579
Publikováno v:
Advances in Intelligent Systems and Computing ISBN: 9789811618420
To solve the problems of strong randomness and fluctuation in wind power forecasting, a novel wind power forecasting model using selective the heterogeneous ensemble (SHeE) method based on local learning and evolutionary multi-objective optimization
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::7f3591bc50ab2ab197b5a7ae83f6b104
https://doi.org/10.1007/978-981-16-1843-7_47
https://doi.org/10.1007/978-981-16-1843-7_47
