A hybrid model of kernel density estimation and quantile regression for GEFCom2014 probabilistic load forecasting
We present a hybrid model combining two types of probabilistic forecast, a kernel density estimation (KDE) and a quantile regression, as part of the load forecasting track of the Global Energy Forecasting Competition 2014 (GEFCom 2014). The KDE method is initially implemented with a time-decay param...
| Main Authors: | , |
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| Format: | Journal article |
| Language: | English |
| Published: |
Elsevier
2015
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| Subjects: |