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Artificial Neural Networks Modeling of Total Dissolved Solid in the Selected Locations on Tigris River, Iraq
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The study aims to predict Total Dissolved Solids (TDS) as a water quality indicator parameter at spatial and temporal distribution of the Tigris River, Iraq by using Artificial Neural Network (ANN) model. This study was conducted on this river between Mosul and Amarah in Iraq on five positions stretching along the river for the period from 2001to 2011. In the ANNs model calibration, a computer program of multiple linear regressions is used to obtain a set of coefficient for a linear model. The input parameters of the ANNs model were the discharge of the Tigris River, the year, the month and the distance of the sampling stations from upstream of the river. The sensitivity analysis indicated that the distance and discharge have the most significant affect on the predicted TDS concentrations. The results showed that a network with (8) hidden neurons was highly accurate in predicting TDS concentration. The correlation coefficient (r), root mean square error (RMSE) and mean absolute percentage error (MAPE) between measured data and model outputs were calculated as 0.975, 113.9 and 11.51%, respectively for testing data sets. Comparisons between final results of ANNs and multiple linear regressions (MLR) showed that the ANNs model could be successfully applied and provides high accuracy to predict TDS concentrations as a water quality parameter.

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Publication Date
Wed Jan 13 2016
Journal Name
University Of Baghdad
Employ Mathematical Model and Neural Networks for Determining Rate Environmental Contamination
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Publication Date
Wed Dec 01 2021
Journal Name
Baghdad Science Journal
Advanced Intelligent Data Hiding Using Video Stego and Convolutional Neural Networks
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Steganography is a technique of concealing secret data within other quotidian files of the same or different types. Hiding data has been essential to digital information security. This work aims to design a stego method that can effectively hide a message inside the images of the video file.  In this work, a video steganography model has been proposed through training a model to hiding video (or images) within another video using convolutional neural networks (CNN). By using a CNN in this approach, two main goals can be achieved for any steganographic methods which are, increasing security (hardness to observed and broken by used steganalysis program), this was achieved in this work as the weights and architecture are randomized. Thus,

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Publication Date
Thu Mar 31 2016
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Permeability Prediction in One of Iraqi Carbonate Reservoir Using Hydraulic Flow Units and Neural Networks
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Permeability determination in Carbonate reservoir is a complex problem, due to their capability to be tight and heterogeneous, also core samples are usually only available for few wells therefore predicting permeability with low cost and reliable accuracy is an important issue, for this reason permeability predictive models become very desirable.

   This paper will try to develop the permeability predictive model for one of  Iraqi carbonate reservoir from core and well log data using the principle of Hydraulic Flow Units (HFUs). HFU is a function of Flow Zone Indicator (FZI) which is a good parameter to determine (HFUs).

   Histogram analysis, probability analysis and Log-Log plot of Reservoir Qua

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Publication Date
Sat Aug 30 2025
Journal Name
Gsc Biological And Pharmaceutical Sciences
A new record of North African catfish Clarias gariepinus (Burchell, 1822) (Siluriformes: Clariidae) in Baghdad from Tigris River
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A single specimen of the African catfish, Clarias gariepinus, was recorded for the first time in Baghdad, Iraq. The specimen was caught during a fish survey to document some local species in northern Baghdad (Al-Rusafa) on March 21, 2023. The total length of the specimen was 43 cm, and its weight was 590 grams. Some biometric measurements of the specimen were studied and found to be consistent with the general characteristics of the African catfish Clarias gariepinus (Burchell, 1822). It is possible that the fish entered Iraqi inland waters, specifically from the Euphrates River via Syria or from the Tigris River via Turkey.

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Publication Date
Sun Feb 24 2019
Journal Name
Iraqi Journal Of Physics
Measuring the concentration of uranium for adults teeth in adjacent areas of Tigris river in Baghdad city using nuclear track detector CR-39
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In this study, the fission track registration technique with the CR-39 detector are using to determination the uranium concentrations for seventeen samples of teeth distributed in four districts in Baghdad City .Five samples taken from both Al-Durra District and Al-Jadiriyia District, Four samples taken from Al-Karrda (Alaatar street) Taken four samples and three samples taken from Al-Zuafrania and by 0.5gm in weight and 1.5 mm in thickness. The uranium concentrations in teeth samples measured by using fission tracks registration in (CR-39) track detector that caused by the bombardment of (U) with thermal neutrons from (241 Am-Be) neutron source that has flux of (5 ×103 n cm-2 s-1). The concen

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Publication Date
Sun Mar 31 2013
Journal Name
Inventi Impact: Artificial Intelligence
SIMULATION OF IDENTIFICATION AND CONTROL OF SCARA ROBOT USING MODIFIED RECURRENT NEURAL NETWORKS
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This paper presents a modified training method for Recurrent Neural Networks. This method depends on the Non linear Auto Regressive (NARX) model with Modified Wavelet Function as activation function (MSLOG) in the hidden layer. The modified model is known as Modified Recurrent Neural (MRN). It is used for identification Forward dynamics of four Degrees of Freedom (4-DOF) Selective Compliance Assembly Robot Arm (SCARA) manipulator robot. This model is also used in the design of Direct Inverse Control (DIC). This method is compared with Recurrent Neural Networks that used Sigmoid activation function (RS) in the hidden layer and Recurrent Neural Networks with Wavelet activation function (RW). Simulation results shows that the MRN model is bett

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Publication Date
Wed Mar 10 2021
Journal Name
Baghdad Science Journal
Environment and lifestyle Fish Qattan in the Euphrates River in central Iraq
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Studied the environment and fish life Qattan in the Euphrates River in central Iraq for the period from September 2002 until 2003 recorded the lowest temperature of the water during the month of January during the month of August ranged salinity ranges between 068

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Publication Date
Mon Mar 08 2021
Journal Name
Baghdad Science Journal
Limnological features Diwanyia River, Iraq
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Monthly water samples from three stations in Diwanya river at Diwanyia city were collected during December 1999 to June 2000. Variables from each stations were determined including ; temperature, pH ,dissolved oxygen, dissolved carbon dioxide , alkalinity ,total hardness, calcium ,magnesium , phosphate, nitrite, nitrate, chlorophyll-a , and total number of phytoplankton .The river considered as fresh water , alkaline ,very hard .The parameters recorded at different values from up and down stream.

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Publication Date
Mon Nov 11 2019
Journal Name
Spe
Modeling Rate of Penetration using Artificial Intelligent System and Multiple Regression Analysis
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Abstract<p>Over the years, the prediction of penetration rate (ROP) has played a key rule for drilling engineers due it is effect on the optimization of various parameters that related to substantial cost saving. Many researchers have continually worked to optimize penetration rate. A major issue with most published studies is that there is no simple model currently available to guarantee the ROP prediction.</p><p>The main objective of this study is to further improve ROP prediction using two predictive methods, multiple regression analysis (MRA) and artificial neural networks (ANNs). A field case in SE Iraq was conducted to predict the ROP from a large number of parame</p> ... Show More
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Publication Date
Sun Mar 01 2020
Journal Name
Journal Of Petroleum Research And Studies
Modeling of Oil Viscosity for Southern Iraqi Reservoirs using Neural Network Method
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The calculation of the oil density is more complex due to a wide range of pressuresand temperatures, which are always determined by specific conditions, pressure andtemperature. Therefore, the calculations that depend on oil components are moreaccurate and easier in finding such kind of requirements. The analyses of twenty liveoil samples are utilized. The three parameters Peng Robinson equation of state istuned to get match between measured and calculated oil viscosity. The Lohrenz-Bray-Clark (LBC) viscosity calculation technique is adopted to calculate the viscosity of oilfrom the given composition, pressure and temperature for 20 samples. The tunedequation of state is used to generate oil viscosity values for a range of temperatu

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