Name
Abstract | ||
|---|---|---|
Run-time forecasting or modeling of domestic appliances has gained more attention in recent years. Comparing currently published works though is difficult due to many differently employed datasets and performance measures. Our long-term aim is to facilitate future work by comparing known approaches on different datasets. Initial results from one method Barbato et al. (in: IEEE International Conference on Smart Grid Communications (SmartGridComm), pp 404–409, 2011) indicate that it is not suitable for the prediction of appliance usage. |
Year | Venue | Keywords |
|---|---|---|
2018 | Computer Science - R&D | Forecasting, Domestic appliance, Experimental comparison |
Field | DocType | Volume |
Data mining,Smart grid,Industrial engineering,Computer science,Real-time computing | Journal | 33 |
Issue | Citations | PageRank |
1-2 | 0 | 0.34 |
References | Authors | |
4 | 4 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Patrick Huber | 1 | 1 | 3.41 |
| Paul Schmieder | 2 | 0 | 0.34 |
| Mario Gerber | 3 | 0 | 0.34 |
| Andreas Rumsch | 4 | 2 | 0.78 |