The aim of the present study is to apply an artificial neural network method for daily, weekly, and monthly wind speed predictions in some parts of the Aegean and Marmara region of Turkey that demonstrate acceptable cross-correlations. The wind data taken with an interval of one hour
were measured by the General Directorate of Electrical Power Resources Survey Administration at four different measuring stations, namely, Gökçeada, Foca, Gelibolu, and Bababurnu. The wind speeds of three different stations were used as input neurons, while the wind speed of the
target station was used as an output neuron in the artificial neural network architecture. The results obtained with this model were compared with the measured data. Errors obtained in this model are within acceptable limits. Results show that the artificial neural network method can successfully
predict the daily, weekly, and monthly wind speed of any target station using the measured data of surrounding stations.
No Reference information available - sign in for access.
No Citation information available - sign in for access.
No Supplementary Data.
No Article Media
artificial neural network;
Document Type: Research Article
Department of Electric and Energy,Adana Vocational School of Higher Education, Cukurova University, Adana, Turkey
Mechanical Engineering Department, Faculty of Engineering and Architecture,Cukurova University, Adana, Turkey
Publication date: March 1, 2013