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A Probabilistic Forecast of Wind Speed using Bayesian Model Averaging
| Content Provider | Semantic Scholar |
|---|---|
| Author | Han, Keunhee Kim, Chansik Kim, Chansoo |
| Copyright Year | 2016 |
| Abstract | This paper used the Bayesian model averaging (BMA) with gamma distribution that takes the form of probability density functions to calibrate probabilistic forecasts of wind speed. We considered the alternative implementation of BMA, which was BMA gamma exchangeable model. This method was applied for forecasting of wind speed over Pyeongchang area using 51 members of the Ensemble Prediction System for Global (EPSG). The performances were evaluated by rank histogram, means absolute error, root mean square error, continuous ranked probability score and skill score. The results showed that BMA gamma exchangeable models performed better in forecasting wind speed, compared to the raw ensemble and ensemble mean. |
| Starting Page | 221 |
| Ending Page | 235 |
| Page Count | 15 |
| File Format | PDF HTM / HTML |
| DOI | 10.14383/cri.2016.11.3.221 |
| Volume Number | 11 |
| Alternate Webpage(s) | http://home.konkuk.ac.kr/cms/Site/UserFiles/Doc/kucri/article/2016_9_2.pdf |
| Alternate Webpage(s) | https://doi.org/10.14383/cri.2016.11.3.221 |
| Language | English |
| Access Restriction | Open |
| Content Type | Text |
| Resource Type | Article |
