Preferred Language
Articles
/
WRaJGIcBVTCNdQwCbjYP
Water Quality Assessment and Sodium Adsorption Ratio Prediction of Tigris River Using Artificial Neural Network
...Show More Authors

Sodium adsorption ratio (SAR) is considered as a measure of the water suitability for irrigation usage. This study examines the effect of the physicochemical parameters on water quality and SAR, which included Calcium(Ca+2), Magnesium(Mg+2), Sodium (Na+), Potassium (K), Chloride (Cl-), Sulfate(SO4-2), Carbonate (CO3-2), Bicarbonate (HCO3-), Nitrate (NO3-), Total Hardness (TH), Total Dissolved Salts (TDS), Electrical Conductivity (EC), degree of reaction (DR), Boron (B) and the monthly and annually flow discharge (Q). The water samples were collected from three stations across the Tigris River in Iraq, which flows through Samarra city (upstream), Baghdad city (central) and the end of Kut city (downstream) for the periods of 2016-2018. Results showed that the water quality of the Tigris River water is within the world health organization (WHO) specifications for drinking water except for Sulfate concentration. An artificial neural network (ANN) was used to develop the model for the three locations to predict SAR. The sum of the squared error function and the coefficient of determination (R2) were used to evaluate the amount of error in predicting values of SAR and performance evaluation of the model. The results showed that the highest value of the coefficient of determination was 0.992, 0.986, and 0.955 for Samarra, Baghdad, and Kut, respectively and the ANN analysis indicated that the prediction of SAR was effected by Sodium for three stations. Thus, the ANN model has been found to provide SAR prediction tool that can be used effectively to describe the suitability of river water quality for irrigation purposes.

Publication Date
Thu Jun 01 2023
Journal Name
Journal Of Engineering
Fault Location of Doukan-Erbil 132kv Double Transmission Lines Using Artificial Neural Network ANN
...Show More Authors

Transmission lines are generally subjected to faults, so it is advantageous to determine these faults as quickly as possible. This study uses an Artificial Neural Network technique to locate a fault as soon as it happens on the Doukan-Erbil of 132kv double Transmission lines network. CYME 7.1-Programming/Simulink utilized simulation to model the suggested network. A multilayer perceptron feed-forward artificial neural network with a back propagation learning algorithm is used for the intelligence locator's training, testing, assessment, and validation. Voltages and currents were applied as inputs during the neural network's training. The pre-fault and post-fault values determined the scaled values. The neural network's p

... Show More
View Publication Preview PDF
Crossref (1)
Crossref
Publication Date
Mon Aug 01 2022
Journal Name
Baghdad Science Journal
Performance Assessment of Solar-Transformer-Consumption System Using Neural Network Approach
...Show More Authors

Solar energy is one of the immeasurable renewable energy in power generation for a green, clean and healthier environment. The silicon-layer solar panels absorb sun energy and converts it into electricity by off-grid inverter. Electricity is transferred either from this inverter or from transformer, consumed by consumption unit(s) available for residential or economic purposes. The artificial neural network is the foundation of artificial intelligence and solves many complex problems which are difficult by statistical methods or by humans. In view of this, the purpose of this work is to assess the performance of the Solar - Transformer - Consumption (STC) system. The system may be in complete breakdown situation due to failure of both so

... Show More
View Publication Preview PDF
Scopus (6)
Crossref (2)
Scopus Clarivate Crossref
Publication Date
Mon Aug 01 2022
Journal Name
Baghdad Science Journal
Optimized Artificial Neural network models to time series
...Show More Authors

        Artificial Neural networks (ANN) are powerful and effective tools in time-series applications. The first aim of this paper is to diagnose better and more efficient ANN models (Back Propagation, Radial Basis Function Neural networks (RBF), and Recurrent neural networks) in solving the linear and nonlinear time-series behavior. The second aim is dealing with finding accurate estimators as the convergence sometimes is stack in the local minima. It is one of the problems that can bias the test of the robustness of the ANN in time series forecasting. To determine the best or the optimal ANN models, forecast Skill (SS) employed to measure the efficiency of the performance of ANN models. The mean square error and

... Show More
View Publication Preview PDF
Scopus (20)
Crossref (8)
Scopus Clarivate Crossref
Publication Date
Wed Mar 10 2021
Journal Name
Baghdad Science Journal
Using of Index Biological Integrity of Phytoplankton (P-IBI) in the Assessment of Water Quality in Don River Section
...Show More Authors

       The multimetric Phytoplankton Index of Biological Integrity (P-IBI) was applied throughout Rostov on Don city (Russia) on 8 Locations in Don River from April – October 2019. The P-IBI is composed from seven metrics: Species Richness Index (SRI), Density of Phytoplankton and total biomass of phytoplankton and Relative Abundance (RA) for blue-green Algae, Green Algae, Bacillariophyceae and Euglenaphyceae Algae. The average P-IBI values fell within the range of (45.09-52.4). Therefore, water throughout the entire study area was characterized by the equally "poor" quality. Negative points of anthropogenic impact detected at the stations are: Above the city of Rostov-on-Don (1 km, higher duct Aksai) was 38.57 i

... Show More
View Publication Preview PDF
Scopus (9)
Crossref (2)
Scopus Clarivate Crossref
Publication Date
Fri Dec 30 2022
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Comparison of Estimation Sonic Shear Wave Time Using Empirical Correlations and Artificial Neural Network
...Show More Authors

Wellbore instability and sand production onset modeling are very affected by Sonic Shear Wave Time (SSW). In any field, SSW is not available for all wells due to the high cost of measuring. Many authors developed empirical correlations using information from selected worldwide fields for SSW prediction. Recently, researchers have used different Artificial Intelligence methods for estimating SSW. Three existing empirical correlations of Carroll, Freund, and Brocher are used to estimate SSW in this paper, while a fourth new empirical correlation is established. For comparing with the empirical correlation results, another study's Artificial Neural Network (ANN) was used. The same data t

... Show More
View Publication Preview PDF
Crossref
Publication Date
Fri Jan 26 2024
Journal Name
Iraqi Journal Of Science
Assessment of pollution with some heavy metals in water, sediments and Barbus xanthopterus fish of the Tigris River–Iraq
...Show More Authors

In this study, four sampling stations were selected on the Tigris River (Baghdad region) in order to determine concentrations, seasonal variation and pollution intensity assessment of heavy metals (Cd, Zn and Mn) in water, sediments and Barbus xanthpterus fish in this river. The study results showed that the mean concentration of dissolved heavy metals (cadmium, zinc and manganese) were 0.004 ppm, 0.023 ppm and 0.007 ppm, respectively. Whereas, their concentrations in sediments were 1.38 ppm, 86 ppm and 231.4 ppm respectively. Irregular seasonal variation for concentrations of these metals in both sediments and water. The mean concentration of these metals in tissues of fish muscles were 0.0043 ppm, 0.0023 ppm and 0.03 ppm for cadmium, z

... Show More
View Publication Preview PDF
Publication Date
Thu May 26 2011
Journal Name
Bulletin Of Environmental Contamination And Toxicology
Chlorophenols in Tigris River and Drinking Water of Baghdad, Iraq
...Show More Authors

study was conducted on a stretch of Tigris river crossing Baghdad city to determine the concentration of some chlorophenols pollutants. Aqueous samples were preliminary enriched about 500 times and the chlorophenols have determined using high performance liquid chromatography HPLC. Limits of detection LOD were (0.007–0.012 mg L-1), relative standard deviations RSD% were 2.4%–5.59% and relative recoveries were 51.06%– 104.07%. The existence of chlorophenols in Tigris river was in the range 0.023–4.596 mg L-1. The developed method suggested in this study can be applied for routine analysis and monitoring of chlorinated phenols in environmental aqueous samples.

View Publication
Scopus (18)
Crossref (13)
Scopus Clarivate Crossref
Publication Date
Wed Jul 05 2017
Journal Name
Https://www.researchgate.net/journal/international-journal-of-science-and-research-ijsr-2319-7064
Evaluation of Water Quality using Bhargava Water Quality Index Method and GIS, Case Study: Euphrates River in Al-Najaf City
...Show More Authors

ENGLISH

Crossref (1)
Crossref
Publication Date
Sat Dec 30 2023
Journal Name
Iraqi Journal Of Science
Water Quality Assessment, Antibiotic Resistance and Plasmid Profiles of Bacteria Isolated from Asa River, Ilorin, Nigeria
...Show More Authors

     Bodies of water are usually being polluted by wastes from domestic and industrial sources thereby making them unfit for use. Hence, this study aimed at assessing the water quality from Asa River, Ilorin, Nigeria in terms of bacteriological and physicochemical parameters. The bacteriological parameters assessed were heterotrophic bacterial count, total coliform, faecal coliform, identification of the isolates, antibiotic resistance patterns, and plasmid profile of the isolates.  Whereas, the assessed physicochemical parameters were pH, total chloride, suspended solid, and total hardness. The heterotrophic bacterial count, total coliform, and faecal coliform counts ranged from 7.6 x 103 to 3.2 x 106 cfu/ml,

... Show More
View Publication Preview PDF
Scopus Crossref
Publication Date
Tue Apr 30 2024
Journal Name
Iraqi Journal Of Science
Crescent Moon Visibility: A New Criterion using Deep learned Artificial Neural-Network
...Show More Authors

     Many authors investigated the problem of the early visibility of the new crescent moon after the conjunction and proposed many criteria addressing this issue in the literature. This article presented a proposed criterion for early crescent moon sighting based on a deep-learned pattern recognizer artificial neural network (ANN) performance. Moon sight datasets were collected from various sources and used to learn the ANN. The new criterion relied on the crescent width and the arc of vision from the edge of the crescent bright limb. The result of that criterion was a control value indicating the moon's visibility condition, which separated the datasets into four regions: invisible, telescope only, probably visible, and certai

... Show More
Preview PDF
Scopus Crossref