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Influence of A River Water Quality on The Efficiency of Water Treatment Using Artificial Neural Network
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Tigris River is the lifeline that supplies a great part of Iraq with water from north to south. Throughout its entire length, the river is battered by various types of pollutants such as wastewater effluents from municipal, industrial, agricultural activities, and others. Hence, the water quality assessment of the Tigris River is crucial in ensuring that appropriate and adequate measures are taken to save the river from as much pollution as possible. In this study, six water treatment plants (WTPs) situated on the two-banks of the Tigris within Baghdad City were Al Karkh; Sharq Dijla; Al Wathba; Al Karama; Al Doura, and Al Wahda from northern Baghdad to its south, that selected to determine the removal efficiency of turbidity and the water quality index used to assess the quality of water for drinking purposes, in addition to finding the model based on past information to predict the quality of treated wastewater produced in each WTP using an artificial neural network (ANN) approach. The selected parameters for this study were turbidity, total hardness, total solids, suspended solids, and alkalinity. The results showed that all the WTPs possessed a high rate of efficiency in the removal of turbidity from raw water. Also, the results of the water quality index for all WTPs were classified over a study period of three years from 2015 to 2017 as being a good water quality and based on these results, the water treatment plants can be considered to be doing efficient water treatment process. The ANN model has been found at all WTPs to have a coefficient of determination (R2) for expected models was more than 0.7 to provide a WQI prediction tool that can be used with a moderate level of predictive acceptance to describe the suitability of WTP water quality for drinking purposes.

Publication Date
Wed Jun 30 2021
Journal Name
Iraqi Geological Journal
Assessment of Groundwater Quality for Drinking Purposes Using Water Quality Index, and Identifying the Affecting Mechanism in Rashdiya, Central Iraq
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Groundwater is an important resource that can be used for various purposes. Various factors can change the chemistry of the GW, such as the chemical composition of an aquifer as well as the leaching of human waste into groundwater. The study area is a barren land covered by some sabkhas, in addition to some agricultural fields. The study aims to assess groundwater quality for drinking purposes using the Water Quality Index. The groundwater is chemically heterogeneous and has a wide quality range from very poor to excellent. Evaporation appears to be the controlling factor among the other shallow waters, while relatively deep water is related to rock-soil dominance. Rocks, land use and land cover have helped control the groundwater q

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Publication Date
Sat Jan 01 2022
Journal Name
Materials Today: Proceedings
Hydraulic behaviour and improving of water quality of the Chibayish Marshes
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Publication Date
Mon Dec 28 2020
Journal Name
International Journal Of Psychosocial Rehabilitation
Predicting the Sporting Achievement in the Pole Vault for Men Using Artificial Neural Networks
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The physical sports sector in Iraq suffers from the problem of achieving sports achievements in individual and team games in various Asian and international competitions, for many reasons, including the lack of exploitation of modern, accurate and flexible technologies and means, especially in the field of information technology, especially the technology of artificial neural networks. The main goal of this study is to build an intelligent mathematical model to predict sport achievement in pole vaulting for men, the methodology of the research included the use of five variables as inputs to the neural network, which are Avarage of Speed (m/sec in Before distance 05 meters latest and Distance 05 meters latest, The maximum speed achieved in t

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Publication Date
Mon Mar 08 2021
Journal Name
Baghdad Science Journal
Bacteriological study of water tributary Zab down and its impact on the environment the waters of the Tigris River
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During the study the current selection seven stations in the Zab River bottom and the Tigris River took samples a month to study the signs of bacterial contamination study coliform and colon fecal Almsobhaat and Almsobhaat Bazah and the total number of bacteria and bacterial gangrene gas causing Knkeran as well as a study to isolate and diagnose some races and types of bacterial pathogens in water or intensityusing the traditional system and the system of intestinal bacteria

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Publication Date
Wed Mar 15 2017
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
The Physical and Chemical Characteristic of Al-Garraf River Water at Waist Province Canal
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 Monthly variations in Physio-chemical parameters of Al-Garraf water in Waist province, one of the main tributaries of the Tigris River to investigate the water quality of the river from August 2014 to January 2015. The study location situated in the southeastern sector of Iraq and surrounded by wide and fertile agricultural lands. Three stations were selected for collecting  samples monthly, samples were taken each month. Station one is located at 500 m of  the AL - KUT Dam. The second is situated at distance of 15 Km away from the former (Kut- Muwafaqiya) and the latter station is located at 18 Km apart from the second one upon entering the river hand Muwafaqiya.  In the present study fourteen physical and chemical

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Publication Date
Sun Apr 23 2017
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
Influence Activation Function in Approximate Periodic Functions Using Neural Networks
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The aim of this paper is to design fast neural networks to approximate periodic functions, that is, design a fully connected networks contains links between all nodes in adjacent layers which can speed up the approximation times, reduce approximation failures, and increase possibility of obtaining the globally optimal approximation. We training suggested network by Levenberg-Marquardt training algorithm then speeding suggested networks by choosing most activation function (transfer function) which having a very fast convergence rate for reasonable size networks.             In all algorithms, the gradient of the performance function (energy function) is used to determine how to

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Publication Date
Tue Dec 31 2024
Journal Name
Iraqi Geological Journal
Geomechanical Modeling and Artificial Neural Network Technique for Predicting Breakout Failure in Nasiriyah Oilfield
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Wellbore instability is one of the major issues observed throughout the drilling operation. Various wellbore instability issues may occur during drilling operations, including tight holes, borehole collapse, stuck pipe, and shale caving. Rock failure criteria are important in geomechanical analysis since they predict shear and tensile failures. A suitable failure criterion must match the rock failure, which a caliper log can detect to estimate the optimal mud weight. Lack of data makes certain wells' caliper logs unavailable. This makes it difficult to validate the performance of each failure criterion. This paper proposes an approach for predicting the breakout zones in the Nasiriyah oil field using an artificial neural network. It

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Scopus Crossref
Publication Date
Mon Apr 03 2023
Journal Name
International Journal Of Online And Biomedical Engineering (ijoe)
An Integrated Grasshopper Optimization Algorithm with Artificial Neural Network for Trusted Nodes Classification Problem
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Wireless Body Area Network (WBAN) is a tool that improves real-time patient health observation in hospitals, asylums, especially at home. WBAN has grown popularity in recent years due to its critical role and vast range of medical applications. Due to the sensitive nature of the patient information being transmitted through the WBAN network, security is of paramount importance. To guarantee the safe movement of data between sensor nodes and various WBAN networks, a high level of security is required in a WBAN network. This research introduces a novel technique named Integrated Grasshopper Optimization Algorithm with Artificial Neural Network (IGO-ANN) for distinguishing between trusted nodes in WBAN networks by means of a classifica

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Publication Date
Tue Jan 17 2017
Journal Name
International Journal Of Science And Research (ijsr)
Detection System of Varicose Disease using Probabilistic Neural Network
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Publication Date
Fri Mar 01 2019
Journal Name
Al-khwarizmi Engineering Journal
Comparison Study of Electromyography Using Wavelet and Neural Network
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In this paper we present a method to analyze five types with fifteen wavelet families for eighteen different EMG signals. A comparison study is also given to show performance of various families after modifying the results with back propagation Neural Network. This is actually will help the researchers with the first step of EMG analysis. Huge sets of results (more than 100 sets) are proposed and then classified to be discussed and reach the final.

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