Application of artificial neural networks for short term wind speed forecasting in Mardin, Turkey

Artificial neural network models were used for short term wind speed forecasting in the Mardin area, located in the Southeast Anatolia region of Turkey. Using data that was obtained from the State Meteorological Service and that encompassed a ten year period, short term wind speed forecasting for the Mardin area was performed. A number of different ANN models were developed in this study. The model with 60 neurons is the most successful model for short term wind speed forecasting. The mean squared error and approximation values for training of this model were 0.378088 and 0.970490, respectively. The ANN models developed in the study have produced satisfactory results. The most successful among those models constitutes a model that can be used by the Mardin Electric Utility Control Centre

The relationship between different age swimmers’ flip turn temporal and kinematic characteristics

This paper analyses the data gathered by measuring the parameters of flip turn executed by 24 swimmers of Kaunas Swimming School. The turning tests were filmed underwater in the deep and shallow side of the pool. The main purpose was to determine relationship between the temporal and kinematic indicators. The correlation parameters varied considering different turn execution conditions and the age of the athlete. The significant correlation was determined between 7.5 m swim in time and 7.5 m swim out from the turn time. It was determined that the longer young athletes took in rotational phase, the longer was the leg stabilization in a deep side of the pool. In the shallow side of the pool the shorter time of swim in of the turn adults took shorter time in turn, push off and gliding phases