Author response to “Discussion on ‘The estimation of monthly mean significant wave heights by using artificial neural network and regression methods’” by Tarkan Erdik

2009 ◽  
Vol 36 (6-7) ◽  
pp. 537
Author(s):  
Kemal Günaydın
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Author Response ◽  
Significant Wave ◽  
Regression Methods ◽  
Wave Heights ◽  
Significant Wave Heights ◽  
Artificial Neural

scholarly journals Prediction of the Pollutants Concentration Using Artificial Neural Network (ANN)

2015 ◽  
Vol 16 (SE) ◽  
pp. 171-180
Author(s):  
Ahmad Mousavian ◽  
Hady Zarei Mahmodabady ◽  
Aboutaleb Ghadami Jadval Ghadam
Keyword(s):  
Neural Network ◽  
Air Pollution ◽  
Artificial Neural Network ◽  
Air Pollutants ◽  
Environmental Issues ◽  
Urban Transport ◽  
Regression Methods ◽  
Tangent Function ◽  
Artificial Neural ◽  
Artificial Neural Network Ann

Air pollution is one of the most important environmental issues that annual causes to mortality large number of people around the world. So, investigating, measuring, and predicting the concentrations of different pollutants in various areas play an important role in preventing the production of this pollutant sand planning to reduce them by people and relevant authorities. One of the new models that play an important role in measuring and predicting pollution is artificial neural network or regression methods. Therefore, this study is trying to predict air pollution in Yasouj by using artificial neural network in 2014. Because the evidences showed that Yasouj due to uncontrolled growth of industrial and urban transport is subject to various air pollutants such as carbon monoxide and particulate matter. Overall, the results of the assessment and prediction of concentration of pollutants of Yasouj by artificial neural network showed that sigmoid transfer function to the hyperbolic tangent function is more efficient in measuring the concentration of pollutants.  

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