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ISSN:2394-3661 | Crossref DOI | SJIF: 5.138 | PIF: 3.854

International Journal of Engineering and Applied Sciences

(An ISO 9001:2008 Certified Online and Print Journal)

Artificial neural network approach for determination of mixing height

( Volume 5 Issue 2,February 2018 ) OPEN ACCESS

Emad Ali Ahmed


Artificial neural networks (ANNs) are one of the areas of artificial intelligence that includes systems that model the way the brain works. In this paper, ANN Model use to determine mixing height from surface meteorological parameters by using MATLAB tools. Weather data for Qena city between 2009 and 2013 are used for training the neural network, while data of 2014 are used for testing.  The results of this study indicated high correlation coefficient (R=0.82) between the measured and predicted output variables. Therefore, the model developed in this work has an acceptable generalization capability and accuracy. As a result, the neural network modeling could effectively simulate and predict mixing height.

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