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The prediction of chemical oxygen demand (COD) or suspended solid (SS) removal using statistical methods and the artifical neural network in the sugar industrial wastewaters
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G. Özkan Et Al. , "The prediction of chemical oxygen demand (COD) or suspended solid (SS) removal using statistical methods and the artifical neural network in the sugar industrial wastewaters," ARPN Journal of Engineering and Applied Sciences , vol.8, no.12, pp.978-983, 2013

Özkan, G. Et Al. 2013. The prediction of chemical oxygen demand (COD) or suspended solid (SS) removal using statistical methods and the artifical neural network in the sugar industrial wastewaters. ARPN Journal of Engineering and Applied Sciences , vol.8, no.12 , 978-983.

Özkan, G., Akin, B. a., & ÖZKAN, G., (2013). The prediction of chemical oxygen demand (COD) or suspended solid (SS) removal using statistical methods and the artifical neural network in the sugar industrial wastewaters. ARPN Journal of Engineering and Applied Sciences , vol.8, no.12, 978-983.

Özkan, Gülay, Banu aliplik Akin, And GÖKSEL ÖZKAN. "The prediction of chemical oxygen demand (COD) or suspended solid (SS) removal using statistical methods and the artifical neural network in the sugar industrial wastewaters," ARPN Journal of Engineering and Applied Sciences , vol.8, no.12, 978-983, 2013

Özkan, Gülay Et Al. "The prediction of chemical oxygen demand (COD) or suspended solid (SS) removal using statistical methods and the artifical neural network in the sugar industrial wastewaters." ARPN Journal of Engineering and Applied Sciences , vol.8, no.12, pp.978-983, 2013

Özkan, G. Akin, B. a. And ÖZKAN, G. (2013) . "The prediction of chemical oxygen demand (COD) or suspended solid (SS) removal using statistical methods and the artifical neural network in the sugar industrial wastewaters." ARPN Journal of Engineering and Applied Sciences , vol.8, no.12, pp.978-983.

@article{article, author={Gülay Özkan Et Al. }, title={The prediction of chemical oxygen demand (COD) or suspended solid (SS) removal using statistical methods and the artifical neural network in the sugar industrial wastewaters}, journal={ARPN Journal of Engineering and Applied Sciences}, year=2013, pages={978-983} }