Investigation of airworthiness in terms of meteorology and artificial neural networks approach in time series for short-term forecasting model: Case of Hasan Polatkan Airport

In this study, meteorological airworthiness criteria were determined using the standards accepted by aviation authoroties and pilot experiences, statistical results were presented using meteorological data covering six years and time series containing daily flight time were obtained. The study is broadened in time series which contain daily total convenient time for flight via estimating for the following days convenient time for flight by make use of artificial neural network methods. For this purpose 10 data sets were setup, 18,240 trainings were performed in 1,824 network models which have various activation functions, various number of hidden layer neurons and various feedback structures and estimation performances were evaluated.