Preferred Language
Articles
/
WhYFXIcBVTCNdQwCtUc_
Application of Artificial Neural Network and GeographicalInformation System Models to Predict and Evaluate the Quality ofDiyala River Water, Iraq
...Show More Authors

This research discusses application Artificial Neural Network (ANN) and Geographical InformationSystem (GIS) models on water quality of Diyala River using Water Quality Index (WQI). Fourteen water parameterswere used for estimating WQI: pH, Temperature, Dissolved Oxygen, Orthophosphate, Nitrate, Calcium, Magnesium,Total Hardness, Sodium, Sulphate, Chloride, Total Dissolved Solids, Electrical Conductivity and Total Alkalinity.These parameters were provided from the Water Resources Ministryfrom seven stations along the river for the period2011 to 2016. The results of WQI analysis revealed that Diyala River is good to poor at the north of Diyala provincewhile it is poor to very polluted at the south of Baghdad City. The selected parameters were subjected to Kruskal-Wallis test for detecting factors contributing to the degradation of water quality and for eliminating independentvariables that exhibit the highest contribution in p-value. The analysis of results revealed that ANN model was goodin predicting the WQI. The confusion matrix for Artificial Neural Model (NNM) gave almost 96% for training, 85.7%for testing and 100% for holdout. In relation to GIS, six color maps of the river have been constructed to give clearimages of the water quality along the river (PDF) Application of Artificial Neural Network and Geographical Information System Models to Predict and Evaluate the Quality of Diyala River Water, Iraq. Available from: https://www.researchgate.net/publication/346028558_Application_of_Artificial_Neural_Network_and_Geographical_Information_System_Models_to_Predict_and_Evaluate_the_Quality_of_Diyala_River_Water_Iraq [accessed Apr 07 2023].

Publication Date
Fri Jun 24 2022
Journal Name
Iraqi Journal Of Science
Validity of Dujaila River Water within Wasit Governorate - Central Iraq
...Show More Authors

Dujaila River is one of the Tigris River branches, its length is 69.45 km, 15 m width and 2.80 m depth, and discharge rate is 42.15m3/Sec. The river provides the water share for 396 thousand Acres.
The primary objective of this study is to evaluate the suitability of water resources, for various purposes in the Dujaila River, Wasit Governorate-central Iraq. Physical and chemical properties have been investigated for 9 surface samples of the period August 2015- March 2016. The tests have been taken for the water major ions, total dissolved solids, electrical conductivity and acidity . Results indicated that the river water is classified as fresh water, according to the total dissolved solid (TDS), which its value ranges between (665-68

... Show More
View Publication Preview PDF
Publication Date
Tue Sep 25 2018
Journal Name
Iraqi Journal Of Science
Using GIS and Remote Sensing to Study Water Quality Changes and Spectral Analysis for AL-Hawizah Marshes, South of Iraq
...Show More Authors

The aim of this research is to measure the changes of Iraqi Marshland's area as well as the changes in the spectral reflectivity water quality, analyzing seasonal difference in AL-Hawizah marshes, South of Iraq using Geographic Information Systems (GIS) and remote sensing techniques. For this paper, the samples were taken at 10 sites along the study area. Satellite images of the 8 Landsat on 20/5/2017, 8/8/2017, 11/10/2017 and 14/12/2017 have been selected in order to study the seasonal changes on the marshes took place during 2017. The reflectance values of red, green, blue and near infrared bands showed that are significantly associated with a seasonal factor. All bands show that reflectivity of the marsh has been affected by locationa

... Show More
View Publication Preview PDF
Publication Date
Fri Feb 01 2019
Journal Name
Environmental Technology & Innovation
The use of Artificial Neural Network (ANN) for modeling of Cu (II) ion removal from aqueous solution by flotation and sorptive flotation process
...Show More Authors

View Publication
Scopus (25)
Crossref (26)
Scopus Clarivate Crossref
Publication Date
Tue Dec 01 2015
Journal Name
Journal Of Engineering
Modeling and Control of Fuel Cell Using Artificial Neural Networks
...Show More Authors

This paper includes an experimental study of hydrogen mass flow rate and inlet hydrogen pressure effect on the fuel cell performance. Depending on the experimental results, a model of fuel cell based on artificial neural networks is proposed. A back propagation learning rule with the log-sigmoid activation function is adopted to construct neural networks model. Experimental data resulting from 36 fuel cell tests are used as a learning data. The hydrogen mass flow rate, applied load and inlet hydrogen pressure are inputs to fuel cell model, while the current and voltage are outputs. Proposed model could successfully predict the fuel cell performance in good agreement with actual data. This work is extended to developed fuel cell feedback

... Show More
View Publication Preview PDF
Publication Date
Fri Jan 01 2021
Journal Name
Ieee Access
Proposition of New Ensemble Data-Intelligence Models for Surface Water Quality Prediction
...Show More Authors

View Publication
Scopus (68)
Crossref (58)
Scopus Clarivate Crossref
Publication Date
Sun Dec 29 2019
Journal Name
Iraqi Journal Of Science
Water quality assessment of Rawanduz River and Gali Ali Beg stream by applied CCME WQI with survey aquatic insects (Ephemeroptera)
...Show More Authors

The population of Ephemeroptera was studied in three selected stations of Rawanduz River (Gali Ali Beg water fall, Rawanduz River and after the junction of these two waters) during the three seasons of spring, summer and autumn in 2016. In addition,sixteen physicochemical parameters (pH, EC, turbidity, DO, BOD5, NO3, TDN, TDP, HCO3-, Hardness, Ca2+, Mg2+, Na+, K+, Cl-, SO42-, Na% and SAR) of water in these stations were estimated and used to calculate the Canadian Council of Ministers of the Environment Water Quality Index (CCME WQI). Eleven species of aquatic insects were identified,which belong to four families of th

... Show More
View Publication Preview PDF
Scopus (10)
Crossref (1)
Scopus Crossref
Publication Date
Wed Jul 05 2017
Journal Name
Neural Computing And Applications
Hybrid soft computing approach for determining water quality indicator: Euphrates River
...Show More Authors

View Publication
Scopus (35)
Crossref (30)
Scopus Clarivate Crossref
Publication Date
Mon Sep 07 2020
Journal Name
Environmental Science And Pollution Research
The biosorption of reactive red dye onto orange peel waste: a study on the isotherm and kinetic processes and sensitivity analysis using the artificial neural network approach
...Show More Authors

View Publication
Scopus (28)
Crossref (23)
Scopus Clarivate Crossref
Publication Date
Wed Dec 01 2021
Journal Name
Journal Of Engineering
Improvement of the Hydrodynamic Behavior and Water Quality Assessment of Al-Chibayish Marshes, Iraq
...Show More Authors

Al-Chibayish Marsh (CM)  is considered as the major part of Central Marshes area of this marsh is 1050 Km². The water quality of these marshes is suffering from salt accumulation due to intensive dam construction, limited supply of water from sources,  climate change impacts, and the absence of outlet flow from these marshes, specifically at low flow periods. So, the current research aims to assess and improve these marshes' hydraulic behavior and water quality and define the best location for outlet drains.  Field measurements and laboratory tests were conducted for two periods (November 2020 and February 2021) to define the (TDS) concentrations at nine different locations. Samples were also examined for water's phy

... Show More
View Publication Preview PDF
Crossref (1)
Crossref
Publication Date
Mon Jun 01 2020
Journal Name
Journal Of Engineering
Artificial Neural Network (ANN) for Prediction of Viscosity Reduction of Heavy Crude Oil using Different Organic Solvents
...Show More Authors

The increase globally fossil fuel consumption as it represents the main source of energy around the world, and the sources of heavy oil more than light, different techniques were used to reduce the viscosity and increase mobility of heavy crude oil. this study focusing on the experimental tests  and modeling with Back Feed Forward Artificial Neural Network (BFF-ANN) of the dilution technique to reduce a  heavy oil viscosity that was collected from the south- Iraq oil fields using organic solvents, organic diluents with different weight percentage  (5, 10 and  20 wt.% )  of  (n-heptane, toluene, and a mixture of  different ratio

... Show More
View Publication Preview PDF
Crossref (3)
Crossref