Classification of Groundwater Quality using Artificial Neural Networks in Safwan and Al-Zubayr in Basra
DOI: 10.23977/acss.2020.040105 | Downloads: 11 | Views: 517
Ahmed Naser Ismael 1, Hamid Ali Abed 2, Majida Ali Abed 3
1 Management Information Systems Department, Basra University, Al-Basrah, Iraq
2 Computer Science Department, Basra University, Al-Basrah, Iraq
3 College of Computers Sciences, Tikrit University, Tikrit, Iraq
Corresponding AuthorHamid Ali Abed
Groundwater in the southern region of Iraq is a completed resource for irrigation and industry. In this study, the groundwater quality of more than 60 wells in the Safwan area and Al-Zubayr district in Basra was calculated using artificial neural networks with feedback. The variables used in the proposed classification and verification model are the physical and chemical variables of groundwater. The taxonomy model demonstrated good performance and accurate taxonomic capacity to facilitate the development and implementation of more effective and sustainable groundwater management strategies in the study area.
KEYWORDSGroundwater Quality, Artificial Neural Networks, Safwan and Al-Zubayr, Basra
CITE THIS PAPER
Ahmed Naser Ismael, Hamid Ali Abed and Majida Ali Abed. Classification of Groundwater Quality using Artificial Neural Networks in Safwan and Al-Zubayr in Basra. Advances in Computer, Signals and Systems (2020) 4: 25-35. DOI: http://dx.doi.org/10.23977/acss.2020.040105.
 Abdalaali, H.H. (2011). "The effect of soil surface mulches, irrigation and nitrogen levels on some soil properties, tomato growth and yield". M.Sc thesis / college of agriculture / university of Basrah / Iraq.
 Al meini, A. K. A. (2010). "proposed index of water quality assessment for irrigation". Eng. & Tech. Journal, 28 (22):6557-6571.
 Al-Abadi, M.A., 2002 : "Optimum management of model of groundwater resources in Safwan-Zubair area, South of Iraq". Unpub. M.Sc. Thesis, College of Science, Univ. of Basra, 110P.
 Al-Aboodi, A.H., 2003 : "A study on Groundwater characteristics in Safwan-Zubair area," Unpub. M.Sc. Thesis, College of Engineering, Uninv. of Basra, 150p.
 Atia, A.M., 2000 :" Hydrogeology of Safwan-Zubair area, South of Iraq", Unpub. M.Sc. Thesis, College of Science, Univ. of Basra, 90P. (In Arabic).
 Dagar, I. C. (2009)."Opportunities for alternate land uses in salty and water scarcity areas." International Journal of Ecology and Environmental Sciences, 35(1):53-66.
 Efe MO (2008), “ Novel neuronal activation functions for feed forward neural networks,” Neural Process Lett , Vol. 28, pp. 63–79..
 Mohammed, M. H. , Mizhir, A. A. and Al-Baʼ aj, A. K. (2010)."Determination of nitrate, nitrite and chloride in ground water of some wells/ Basrah, south of Iraq." Scientific Basrah Research, 36(1):59-64.
 Majida A. A., Hamid A. A.(2015)"High Accuracy Arabic Handwritten Characters Recognition Using Error Back Propagation Artificial Neural Networks",(IJACSA) International Journal of Advanced Computer Science and Applications,Vol. 6, No. 2,
 Semra.,Recep (2018) " Modelling Nitrate Prediction of Groundwater and Surface Water Using Artificial Neural Networks",Vol 2,No. 21:312-325.