Composite quantile regression extreme learning machine with feature selection for short-term wind speed forecasting: A new approach
Review articleOpen access
2017/11/01 Full-length article DOI: 10.1016/j.enconman.2017.09.029
Journal: Energy Conversion and Management
Highlights•Proposed a hybrid architecture based on CQR-ORELM model for wind speed forecasting.•A hybrid PSOGSA is used for feature selection and parameter optimization.•A TVF-EMD approach is firstly exploited to decompose the original wind speed signal.•Predictive probabilistic density is estimated using different quantile results.
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