M. A. Ghorbani Et Al. , "Deep learning under H2O framework: A novel approach for quantitative analysis of discharge coefficient in sluice gates," Journal of Hydroinformatics , vol.22, pp.1603-1619, 2020
Ghorbani, M. A. Et Al. 2020. Deep learning under H2O framework: A novel approach for quantitative analysis of discharge coefficient in sluice gates. Journal of Hydroinformatics , vol.22 , 1603-1619.
Ghorbani, M. A., Salmasi, F., Saggi, M. K., Bhatia, A. S., Kahya, E., & Norouzi, R., (2020). Deep learning under H2O framework: A novel approach for quantitative analysis of discharge coefficient in sluice gates. Journal of Hydroinformatics , vol.22, 1603-1619.
Ghorbani, Mohammad Et Al. "Deep learning under H2O framework: A novel approach for quantitative analysis of discharge coefficient in sluice gates," Journal of Hydroinformatics , vol.22, 1603-1619, 2020
Ghorbani, Mohammad A. Et Al. "Deep learning under H2O framework: A novel approach for quantitative analysis of discharge coefficient in sluice gates." Journal of Hydroinformatics , vol.22, pp.1603-1619, 2020
Ghorbani, M. A. Et Al. (2020) . "Deep learning under H2O framework: A novel approach for quantitative analysis of discharge coefficient in sluice gates." Journal of Hydroinformatics , vol.22, pp.1603-1619.
@article{article, author={Mohammad Ali Ghorbani Et Al. }, title={Deep learning under H2O framework: A novel approach for quantitative analysis of discharge coefficient in sluice gates}, journal={Journal of Hydroinformatics}, year=2020, pages={1603-1619} }