The identification of future water need through artificial neural networks and fuzzy logic methods in Turkey

In this thesis, the future water need of Turkey is estimated through the methods of Artificial Neural Networks and Fuzzy Logic. The data taken from Turkish statistics. Institution is established in (0-1) interval using fuzzy artificial neural network. Later, using 80 percent of the data. It is made for artificial neural network to learn relationship between data. After realizing this with the rest of 20 percent of the data level of learning realized by artificial neural network is tested. The desired level is caught. Then the water need of Turkey in following year is analyzed using data obtained. As a last step, the results are given in tables, graphs and the changes in water need of Turkey are analyzed according to years.