Forecasting PM 10 in the Bay of Algeciras Based on Regression Models
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- Masseran, N. & Razali, A.M. & Ibrahim, K. & Wan Zin, W.Z., 2012. "Evaluating the wind speed persistence for several wind stations in Peninsular Malaysia," Energy, Elsevier, vol. 37(1), pages 649-656.
- Foley, Aoife M. & Leahy, Paul G. & Marvuglia, Antonino & McKeogh, Eamon J., 2012. "Current methods and advances in forecasting of wind power generation," Renewable Energy, Elsevier, vol. 37(1), pages 1-8.
- Li, Gong & Shi, Jing & Zhou, Junyi, 2011. "Bayesian adaptive combination of short-term wind speed forecasts from neural network models," Renewable Energy, Elsevier, vol. 36(1), pages 352-359.
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Keywords
time-series forecasting; regression models; artificial neural networks; on-site measurements; exogenous information;All these keywords.
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