Name
Abstract | ||
|---|---|---|
In this article, a new approach to short-term load forecasting is proposed using a multicolumn radial basis function neural network (MCRN). The advantage of this new approach over similar models in speed and accuracy is also discussed, especially in regards to renewable generation forecasting. Because weather and seasonal effects have a direct impact not only on load demand but also on renewable e... |
Year | DOI | Venue |
|---|---|---|
2020 | 10.1109/TIE.2019.2939988 | IEEE Transactions on Industrial Electronics |
Keywords | DocType | Volume |
Load forecasting,Forecasting,Training,Load modeling,Predictive models,Meteorology,Biological neural networks | Journal | 67 |
Issue | ISSN | Citations |
8 | 0278-0046 | 0 |
PageRank | References | Authors |
0.34 | 0 | 5 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Ammar O. Hoori | 1 | 1 | 0.68 |
| Ahmad Al Kazzaz | 2 | 0 | 0.34 |
| Rameez Khimani | 3 | 0 | 0.34 |
| Yuichi Motai | 4 | 230 | 24.68 |
| Alex J. Aved | 5 | 0 | 0.34 |