In this task, you are given a part of an article. Your task is to generate headline (title) for this text. Preferred headlines are under fifteen words.

To mitigate the uncertainty of variable renewable<lb>resources, two off-the-shelf machine learning tools are deployed<lb>to forecast the solar power output of a solar photovoltaic system.<lb>The support vector machines generate the forecasts and the<lb>random forest acts as an ensemble learning method to combine<lb>the forecasts. The common ensemble technique in wind and solar<lb>power forecasting is the blending of meteorological data from<lb>several sources. In this study though, the present and the past<lb>solar power forecasts from several models, as well as the<lb>associated meteorological data, are incorporated into the random<lb>forest to combine and improve the accuracy of the day-ahead<lb>solar power forecasts. The performance of the combined model is<lb>evaluated over the entire year and compared with other<lb>combining techniques. KeywordsEnsemble learning, post-processing, random forest,<lb>solar power, support vector regression.
Random Forest Ensemble of Support Vector Regression Models for Solar Power Forecasting