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Application of Artificial Neural Network for Predicting Iron Concentration in the Location of Al-Wahda Water Treatment Plant in Baghdad City
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Iron is one of the abundant elements on earth that is an essential element for humans and may be a troublesome element in water supplies.  In this research an AAN model was developed to predict iron concentrations in the location of Al- Wahda water treatment plant in Baghdad city by water quality assessment of iron concentrations at seven WTPs up stream Tigris River. SPSS software was used to build the ANN model. The input data were iron concentrations in the raw water for the period 2004-2011. The results indicated the best model predicted Iron concentrations at Al-Wahda WTP with a coefficient of determination 0.9142. The model used one hidden layer with two nodes and the testing error was 0.834. The ANN model could be used to predict future iron concentrations as the results from the verification of the ANN model for years 2012 and 2013 indicated good accuracy with a coefficient of determination R2 = 0.8965.

 

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Publication Date
Thu Apr 01 2021
Journal Name
Complexity
Bayesian Regularized Neural Network Model Development for Predicting Daily Rainfall from Sea Level Pressure Data: Investigation on Solving Complex Hydrology Problem
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Prediction of daily rainfall is important for flood forecasting, reservoir operation, and many other hydrological applications. The artificial intelligence (AI) algorithm is generally used for stochastic forecasting rainfall which is not capable to simulate unseen extreme rainfall events which become common due to climate change. A new model is developed in this study for prediction of daily rainfall for different lead times based on sea level pressure (SLP) which is physically related to rainfall on land and thus able to predict unseen rainfall events. Daily rainfall of east coast of Peninsular Malaysia (PM) was predicted using SLP data over the climate domain. Five advanced AI algorithms such as extreme learning machine (ELM), Bay

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Scopus (24)
Crossref (17)
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Publication Date
Thu Feb 01 2018
Journal Name
Journal Of Engineering
Upgrading of Alum Preparation and Dosing Unit for Sharq Dijla Water Treatment Plant by Using Programmable Logic Controller System
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One of the important units in Sharq Dijla Water Treatment Plant (WTP) first and second extensions are the alum solution preparation and dosing unit. The existing operation of this unit accomplished manually starting from unloading the powder alum in the preparation basin and ending by controlling the alum dosage addition through the dosing pumps to the flash mix chambers. Because of the modern trend of monitoring and control the automatic operation of WTPs due to the great benefits that could be gain from optimum equipment operation, reducing the operating costs and human errors. This study deals with how to transform the conventional operation to an automatic monitoring and controlling system depending on a Programmable

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Publication Date
Sun Jun 30 2013
Journal Name
Al-khwarizmi Engineering Journal
Estimated Outlet Temperatures in Shell-and-Tube Heat Exchanger Using Artificial Neural Network Approach Based on Practical Data
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The objective of this study is to apply Artificial Neural Network for heat transfer analysis of shell-and-tube heat exchangers widely used in power plants and refineries. Practical data was obtained by using industrial heat exchanger operating in power generation department of Dura refinery. The commonly used Back Propagation (BP) algorithm was used to train and test networks by divided the data to three samples (training, validation and testing data) to give more approach data with actual case. Inputs of the neural network include inlet water temperature, inlet air temperature and mass flow rate of air. Two outputs (exit water temperature to cooling tower and exit air temperature to second stage of air compressor) were taken in ANN.

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Publication Date
Sun Mar 05 2017
Journal Name
Baghdad Science Journal
Screening of Epiphytic Algae on the Aquatic Plant Phragmites australis inhabiting Tigris River in Al-Jadria Site, Baghdad, Iraq
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The present work included qualitative study of epiphytic algae on dead and living stems, leaves of the aquatic plant Phragmitesaustralis Trin ex Stand, in Tigris River in AL- Jadria Site in Baghdad during Autumn 2014, Winter 2015, Spring 2015, and Summer 2015. The physical and chemical parameters of River’s water were studied (water temperature, pH, electric conductivity, Salinity, TSS, TDS, turbidity, light intensity, dissolve oxygen, BOD5, alkalinity, total hardness, calcium, magnesium and plant nutrient). A total of 142 isolates of epiphytic algae were identified. Diatoms were dominant by 117 isolates followed by Cyanobacteria (13isolates), Chlorophyta (11 isolates) and Rhodophyta (1 isolate), Variations in the isolates number were rec

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Scopus (14)
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Publication Date
Wed Jun 30 2010
Journal Name
Al-kindy College Medical Journal
Assessment of workplace hazards among working children in al amen city, Baghdad
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Back ground: One out of six children in the
world today is involved in child labor, doing
work that is damaging to his or her mental,
physical and emotional development.
Objective: Assessment of some health
problems among the studied working children.
Method; A cross-sectional study was
conducted in Al Amen Primary Health Care
(PHCC) during the period from January to
August 2009, a sample of 6048 children were
selected randomly(3218girls and2866 boys age
between 5-17 years ) and interviewed to collect
information using a structured questionnaire
form, information related to different aspects
of child labor prevention were included in the
form as well as a general medical examination
and lab

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Publication Date
Sat Jan 01 2022
Journal Name
The 2nd Universitas Lampung International Conference On Science, Technology, And Environment (ulicoste) 2021
A comparison between IRI-2016 and ASAPS models for predicting foF2 ionospheric parameter over Baghdad city
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Scopus (2)
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Publication Date
Fri Dec 30 2022
Journal Name
Eastern-european Journal Of Enterprise Technologies
Experimental investigation and modelling of residual stresses in face milling of Al-6061-T3 using neural network
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Milling process is a common machining operation that is used in the manufacturing of complex surfaces. Machining-induced residual stresses (RS) have a great impact on the performance of machined components and the surface quality in face milling operations with parameter cutting. The properties of engineering material as well as structural components, specifically fatigue life, deformation, impact resistance, corrosion resistance, and brittle fracture, can all be significantly influenced by residual stresses. Accordingly, controlling the distribution of residual stresses is indeed important to protect the piece and avoid failure. Most of the previous works inspected the material properties, tool parameters, or cutting parameters, bu

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Scopus (4)
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Publication Date
Sun Oct 10 2021
Journal Name
Journal Of Kirkuk University For Agricultural Sciences
Effect of Drought Stress (Water Deficit) and Plant Density on Productivity of Water and Zea mays (Baghdad Varieties) in Middle Region of Iraq
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The objective of this study was to investigate the drought stress and plant density possibility on water productivity and grain yield of maize (Zea mays L.) (Planting Baghdad 3 synthetic varieties), Field experiment was conducted at Abu Ghraib Research Station (Baghdad) during spring and Autumn seasons of 2016 using a randomized complete block design arranged in split plot with three replications. Three irrigation treatment included: irrigation after depletion 50% of available water (T1), irrigation after depletion 75% of available water (T2) and irrigation after depletion 90% of available water (T3) in the main plots and three plant density which were: 1 seeds hill-1 (D1) giving a uniform plant density of 66666 plants ha-1 , 2 seeds hill1

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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
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Scopus (37)
Crossref (38)
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Publication Date
Tue Sep 01 2020
Journal Name
Baghdad Science Journal
Developing Arabic License Plate Recognition System Using Artificial Neural Network and Canny Edge Detection
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In recent years, there has been expanding development in the vehicular part and the number of vehicles moving on the roads in all the sections of the country. Arabic vehicle number plate identification based on image processing is a dynamic area of this work; this technique is used for security purposes such as tracking of stolen cars and access control to restricted areas. The License Plate Recognition System (LPRS) exploits a digital camera to capture vehicle plate numbers is used as input to the proposed recognition system. Basically, the proposed system consists of three phases, vehicle license plate localization, character segmentation, and character recognition, the License Plate (LP) detection is presented using canny edge detection

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