IEEE 17th Signal Processing and Communications Applications Conference, Antalya, Turkey, 9 - 11 April 2009, pp.117-118
Wind speed prediction is an important issue in wind related engineering studies. However, the wind data has random behavior like other meteorological events. Therefore, it is difficult to apply conventional statistical approaches. On the other hand, wind speed data has an important feature; large fluctuations from a wind state to a significantly different level is relatively seldom. This feature leads to some patterns that should be exemined in detail. In this study, a novel approach for wind speed modeling using Mycielski algorithm that considers this important future is demonstrated. Developed procedure, predicts future values of wind data by analysing repeatings in the history of data and assumes that the history will be structurely repeated in the future. The prediction capability of the procedure is tested using wind speed data obtained from 2 cities in Turkey: Izmir and Antalya. Reasonable prediction results are obtained and analysis results are reported.