Zobrazeno 1 - 5
of 5
pro vyhledávání: '"Rafa h. Al-Suhili"'
Autor:
Rafa H. Al-Suhili, Nawbahar F. Mustafa
Publikováno v:
Journal of Engineering, Vol 20, Iss 07 (2023)
A multivariate multisite hydrological data forecasting model was derived and checked using a case study. The philosophy is to use simultaneously the cross-variable correlations, cross-site correlations and the time lag correlations. The case study is
Externí odkaz:
https://doaj.org/article/40d8cfe162994dd4bd6d2c255da39a40
Publikováno v:
Journal of Engineering, Vol 18, Iss 05 (2023)
Optimum allocation of water for restoration of Iraqi marshes is essential for different related authorities. Abo-Ziriq marsh area about 120 km2 is situated 40 km east of Al-Nassryia city. After comparing the measured annual water qualities with the I
Externí odkaz:
https://doaj.org/article/957c2dc2535140938e9837553bb8a17e
Multi-Sites Multi-Variables Forecasting Model for Hydrological Data using Genetic Algorithm Modeling
Autor:
Rafa H. Al-Suhili
Publikováno v:
Journal of Engineering, Vol 21, Iss 3, Pp 54-72 (2015)
A two time step stochastic multi-variables multi-sites hydrological data forecasting model was developed and verified using a case study. The philosophy of this model is to use the cross-variables correlations, cross-sites correlations and the two st
Externí odkaz:
https://doaj.org/article/9836d9db0e464d29b8120e3f1b88b667
Publikováno v:
Journal of University of Babylon, Vol 25, Iss 4, Pp 1381-1391 (2017)
This paper provides Artificial Neural Networks model versions for forecasting the monthly averages of some chemical water quality parameters of Shatt Al-Hilla River, which is located at Hilla City, south of Iraq. The water quality parameters investig
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doajarticles::2d7a94ce8f544d5c02d4213ff7d1cf0d
http://www.uobjournal.com/papers/uobj_paper_2017_52543505.pdf
http://www.uobjournal.com/papers/uobj_paper_2017_52543505.pdf
Autor:
Rafa H. Al-Suhili, Rizgar A. Karim
Publikováno v:
International Journal of Water. 9:194
Five ANN model versions were developed for the daily inflow forecasting to Dukan reservoir in Iraq. These models are dependent on the preceding days' lags (1, 2, 3, 4, and 5), respectively. The model versions forecasting correlation coefficients were
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::f240398c85b513aaa68d22ee4164c483
https://doi.org/10.1504/ijw.2015.068961
https://doi.org/10.1504/ijw.2015.068961