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
Fri Jan 01 2021
Journal Name
Advances In Intelligent Systems And Computing
Optimal Prediction Using Artificial Intelligence Application
...Show More Authors

View Publication
Scopus (16)
Crossref (15)
Scopus Crossref
Publication Date
Thu Sep 01 2022
Journal Name
Journal Of Engineering
Assessment of Thermal Pollution at Selected Stretch of Tigris River in Baghdad by Field Observations and Numerical Simulations
...Show More Authors

Although many technological improvements are occurring in power production worldwide, power plants in third world countries are still using old technologies that are causing thermal pollution to the water bodies. Power facilities that dump hot water into water bodies are damaging aquatic life. In the study, the impact of the Al Dora thermal power plant on a nearby stretch of Tigris River in Baghdad city was assessed by measuring the temperature of the disposed of hot water in various cross-sections of the selected stretch of Tigris River, including measuring the thermal mixing length. The measurements were conducted in winter, spring, and summer. For field measurements, it was found that the impact of recovery distances

... Show More
View Publication Preview PDF
Crossref
Publication Date
Wed Jan 01 2025
Journal Name
Aip Conference Proceedings
Predicting biochemical oxygen demand at Al-Rustumiya wastewater treatment plant inlet using the artificial neural network
...Show More Authors

View Publication
Scopus Crossref
Publication Date
Sun Jun 04 2017
Journal Name
Baghdad Science Journal
Assessment of Water Quality and Trophic Status of Duhok Lake Dam
...Show More Authors

This study is conducted in order to, investigate the trophic state of Duhok Lake Dam located within Duhok city, Iraq. Water samples are collected seasonally from three monitored sites during 2011. The parameters used for assessing water quality and trophic status level include: water temperature, pH, EC, TDS, DO, BOD5, nutrients, Secchi disk transparency, and chlorophyll a. The results reveal that DO is above 5 mg.l-1 in all sites, BOD5 value is within permissible level for domestic uses. Water quality considered as a hard type. High sulfate concentration is recorded during the study period. Trophic state shows that water type is classified as mesotrophic during autumn season, while it is regarded as eutrophic in other seasons. TDN/TDP rati

... Show More
View Publication Preview PDF
Scopus (16)
Crossref (1)
Scopus Crossref
Publication Date
Mon Apr 09 2018
Journal Name
Al-khwarizmi Engineering Journal
Neural Network Modeling of Cutting Force and Chip Thickness Ratio for Turning Aluminum Alloy 7075-T6
...Show More Authors

The turning process has various factors, which affecting machinability and should be investigated. These are surface roughness, tool life, power consumption, cutting temperature, machining force components, tool wear, and chip thickness ratio. These factors made the process nonlinear and complicated. This work aims to build neural network models to correlate the cutting parameters, namely cutting speed, depth of cut and feed rate, to the machining force and chip thickness ratio. The turning process was performed on high strength aluminum alloy 7075-T6. Three radial basis neural networks are constructed for cutting force, passive force, and feed force. In addition, a radial basis network is constructed to model the chip thickness ratio. T

... Show More
View Publication Preview PDF
Crossref (3)
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
Sat Dec 01 2018
Journal Name
Indian Journal Of Ecology
Classification of al-hammar marshes satellite images in Iraq using artificial neural network based on coding representation
...Show More Authors

Scopus (2)
Scopus
Publication Date
Thu Mar 21 2019
Journal Name
J. Eng. Appl. Sci
Developing an Arabic handwritten recognition system by means of artificial neural network
...Show More Authors

The matter of handwritten text recognition is as yet a major challenge to mainstream researchers. A few ways deal with this challenge have been endeavored in the most recent years, for the most part concentrating on the English pre-printed or handwritten characters space. Consequently, the need to effort a research concerning to Arabic texts handwritten recognition. The Arabic handwriting presents unique technical difficulties because it is cursive, right to left in writing and the letters convert its shapes and structures when it is putted at initial, middle, isolation or at the end of words. In this study, the Arabic text recognition is developed and designed to recognize image of Arabic text/characters. The proposed model gets a single l

... Show More
Publication Date
Thu Mar 31 2022
Journal Name
Iraqi Geological Journal
Development of New Models to Determine the Rheological Parameters of Water-Based Drilling Fluid using Artificial Neural Networks
...Show More Authors

It is well known that drilling fluid is a key parameter for optimizing drilling operations, cleaning the hole, and managing the rig hydraulics and margins of surge and swab pressures. Although the experimental works represent valid and reliable results, they are expensive and time consuming. In contrast, continuous and regular determination of the rheological fluid properties can perform its essential functions during good construction. The aim of this study is to develop empirical models to estimate the drilling mud rheological properties of water-based fluids with less need for lab measurements. This study provides two predictive techniques, multiple regression analysis and artificial neural networks, to determine the rheological

... Show More
Crossref
Publication Date
Mon Dec 20 2021
Journal Name
Bulletin Of The Iraq Natural History Museum (p-issn: 1017-8678 , E-issn: 2311-9799)
IMPACT OF THARTHAR ARM WATER ON COMPOSITION AND DIVERSITY OF COPEPODA IN TIGRIS RIVER, NORTH OF BAGHDAD CITY, IRAQ
...Show More Authors

This study is considered to be the first on this sector of Tigris River after 2003, to evaluate the effect of Tharthar Arm on the composition and diversity of Copepoda in Tigris River. Six sampling sites were selected; two on the Tharthar Arm and four sites along the Tigris River, one before the confluence as a control site and the others downstream the confluence; thirty-five copepod taxa were recorded, 34 taxa in the Tigris River and 25 taxa in the Tharthar Arm.
The highest density of Copepoda was in site 2 at Tharthar Arm was 265584.2 Ind./m3 lead to an increasing in Copepoda density in Tigris River from 63878.2 Ind./m3 in site 1 before the confluence to 127198.3 Ind./m3 in site 4 immediately downstream the confluence. Also, the me

... Show More
View Publication Preview PDF
Scopus (11)
Crossref (2)
Scopus Crossref