یک روش داده کاوی: تجزیه و تحلیل سرعت باد و داده دوره تابشی در ترکیه برای نصب و راه اندازی نیروگاه های بادی و خورشیدی

This paper focuses on the similarity, feasibility and numerical analyses of 75 cities in Turkey based on the monthly average wind speed and insolation period data. The nearest and the farest neighbor algorithms are used as agglomerative hierarchical clustering methods with Euclidean, Manhattan and Minkowski distance metrics in the stage of making the similarity and feasibility analyses. The maximum cophenetic correlation coefficient is achieved by the nearest neighbor algorithm with the Minkowski distance metric in the similarity and feasibility analyses. On the other hand, graphical representations of the monthly average wind speed and insolation period data are utilized for making the numerical analysis. The highest annual average wind speed and insolation period are obtained as 3.88 m/s and 8.45 h/day, respectively. Overall, many inferences were achieved in acceptable and efficient limits for wind and solar energy.