University of Tabriz Water and Soil Science 2008-5133 20 3 2010 10 23 Estimation of Maximum, Mean and Minimum Air Temperature in Tabriz City Using Artificial Intelligent Methods Estimation of Maximum, Mean and Minimum Air Temperature in Tabriz City Using Artificial Intelligent Methods 87 104 1335 FA MA Ghorbani J Shiri H Kazemi Journal Article 2014 05 12 Estimating air temperature is one of the important issues in agricultural planning and in water<br />resources management which can be accomplished by using different methods such as empirical,<br />semi-empirical and intelligent methods. In the present study, Adaptive Neuro Fuzzy Inference<br />System, Artificial Neural Networks and Genetic Programming were used to estimate air<br />temperature in the synoptic station of Tabriz City, northwest of Iran. Considering the statistical<br />indices, all three models were able to estimate accurately minimum, mean and maximum air<br />temperature. In spite of slight differences in the prediction accuracy and errors by the models,<br />Adaptive Neuro Fuzzy Inference System, Artificial Neural Networks and Genetic Programming<br />were in the order of priority. Also explicit solutions that show the relation between input and output<br />variables are presented based on Genetic Programming. This adds to the superiority of Genetic<br />Programming over the other two models. Estimating air temperature is one of the important issues in agricultural planning and in water<br />resources management which can be accomplished by using different methods such as empirical,<br />semi-empirical and intelligent methods. In the present study, Adaptive Neuro Fuzzy Inference<br />System, Artificial Neural Networks and Genetic Programming were used to estimate air<br />temperature in the synoptic station of Tabriz City, northwest of Iran. Considering the statistical<br />indices, all three models were able to estimate accurately minimum, mean and maximum air<br />temperature. In spite of slight differences in the prediction accuracy and errors by the models,<br />Adaptive Neuro Fuzzy Inference System, Artificial Neural Networks and Genetic Programming<br />were in the order of priority. Also explicit solutions that show the relation between input and output<br />variables are presented based on Genetic Programming. This adds to the superiority of Genetic<br />Programming over the other two models. https://water-soil.tabrizu.ac.ir/article_1335_57c82692c43e487a7974a2215f9db00f.pdf