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AI-Driven Prediction of Average Per Capita GDP: Exploring Linear and Nonlinear Statistical Techniques
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Average per capita GDP income is an important economic indicator. Economists use this term to determine the amount of progress or decline in the country's economy. It is also used to determine the order of countries and compare them with each other. Average per capita GDP income was first studied using the Time Series (Box Jenkins method), and the second is linear and non-linear regression; these methods are the most important and most commonly used statistical methods for forecasting because they are flexible and accurate in practice. The comparison is made to determine the best method between the two methods mentioned above using specific statistical criteria. The research found that the best approach is to build a model for predicting Iraq’s average GDP per capita income by relying on the amounts of average GDP per capita income in the past years (1981-2020). The researcher found that in a second way, it became clear that the non-linear regression model of the Asian model was the best model representing (average per capita GDP income) in Iraq, and this model was used to predict the period (20221-2027). When comparing the two methods of projected amounts up to 2027, it was found that the best method was the second based on the indicator mean absolute percentage error (MAPE) because he has the least value.

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Publication Date
Mon Oct 01 2018
Journal Name
Journal Of Engineering
Water Quality Assessment and Total Dissolved Solids Prediction using Artificial Neural Network in Al-Hawizeh Marsh South of Iraq
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The Iraqi marshes are considered the most extensive wetland ecosystem in the Middle East and are located in the middle and lower basin of the Tigris and Euphrates Rivers which create a wetlands network and comprise some shallow freshwater lakes that seasonally swamped floodplains. Al-Hawizeh marsh is a major marsh located east of Tigris River south of Iraq. This study aims to assess water quality through water quality index (WQI) and predict Total Dissolved Solids (TDS) concentrations in Al-Hawizeh marsh based on artificial neural network (ANN). Results showed that the WQI was more than 300 for years 2013 and 2014 (Water is unsuitable for drinking) and decreased within the range 200-300 in years 2015 and 2016 (Very poor water). The develope

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Publication Date
Wed May 31 2023
Journal Name
Iraqi Geological Journal
Studying the Effect of Permeability Prediction on Reservoir History Matching by Using Artificial Intelligence and Flow Zone Indicator Methods
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The map of permeability distribution in the reservoirs is considered one of the most essential steps of the geologic model building due to its governing the fluid flow through the reservoir which makes it the most influential parameter on the history matching than other parameters. For that, it is the most petrophysical properties that are tuned during the history matching. Unfortunately, the prediction of the relationship between static petrophysics (porosity) and dynamic petrophysics (permeability) from conventional wells logs has a sophisticated problem to solve by conventional statistical methods for heterogeneous formations. For that, this paper examines the ability and performance of the artificial intelligence method in perme

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Publication Date
Tue Mar 20 2018
Journal Name
Day 2 Wed, March 21, 2018
Numerical Approach for the Prediction of Formation and Hydraulic Fracture Properties Considering Elliptical Flow Regime in Tight Gas Reservoirs
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Abstract<p>As tight gas reservoirs (TGRs) become more significant to the future of the gas industry, investigation into the best methods for the evaluation of field performance is critical. While hydraulic fractured well in TRGs are proven to be most viable options for economic recovery of gas, the interpretation of pressure transient or well test data from hydraulic fractured well in TGRs for the accurate estimation of important reservoirs and fracture properties (e.g. fracture length, fracture conductivity, skin and reservoir permeability) is rather very complex and difficult because of the existence of multiple flow profiles/regimes. The flow regimes are complex in TGRs due to the large hydraulic fractures n</p> ... Show More
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Publication Date
Sun Apr 01 2018
Journal Name
Journal Of Engineering/
Water quality assessment and total dissolved solids prediction using artificial neural network in Al-Hawizeh marsh south of Iraq
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The Iraqi marshes are considered the most extensive wetland ecosystem in the Middle East and are located in the middle and lower basin of the Tigris and Euphrates Rivers which create a wetlands network and comprise some shallow freshwater lakes that seasonally swamped floodplains. Al-Hawizeh marsh is a major marsh located east of Tigris River south of Iraq. This study aims to assess water quality through water quality index (WQI) and predict Total Dissolved Solids (TDS) concentrations in Al-Hawizeh marsh based on artificial neural network (ANN). Results showed that the WQI was more than 300 for years 2013 and 2014 (Water is unsuitable for drinking) and decreased within the range 200-300 in years 2015 and 2016 (Very poor water). The

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Publication Date
Wed May 29 2019
Journal Name
Iraqi Journal Of Physics
Analysis the effect of economic conditions on the vegetative change in Baghdad using GIS and remote sensing techniques
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The study of vegetative change of cities is one of the most important studies related to human life because of its direct correlation with the temporal conditions that occur. These include the economic problems that force people to move and look for job opportunities in the city, which leads to an increase in the population density of cities, especially for cities with an important economic and administrative location as in the capital city of Baghdad. In this study, the effect of the increasing in population density was analyzed on the urban planning of Baghdad city. The decreasing in vegetation was due to the increasing of urban areas on the outskirts of the city, which led to an increase in its area. Moreover, urban cities increased t

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Publication Date
Sun Apr 01 2018
Journal Name
Journal Of Economics And Administrative Sciences
Using modern techniques for determining the location of marketing outlet for product of the state company for vegetables oil
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Were arranged this study on two sections, which included first section comparison between markets proposed through the use of transport models and the use of the program QSB for less costs , dependant the optimal solution  to chose the suggested market  to locate new market that achieve lower costs in the transport of goods from factories (ALRasheed ,ALAmeen , AlMaamun ) to points of sale, but the second part has included comparison of all methods of transport (The least cost method ,Vogels method , Results Approximations method , Total method) depending on the agenda of transport, which includes the market proposed selected from the first section and choose the way in which check the solution first best suited in terms

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Publication Date
Fri Nov 27 2020
Journal Name
Journal Of Physics: Conference Series
Investigation of the State Vectors and Prediction of the Orbital Elements for Spot-6 Satellite during 1300 periods with Perturbations
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Abstract<p>Computer simulations were carried out to investigate the dependence of the main perturbation parameters (Sun and Moon attractions, solar radiation pressure, atmosphere drag, and geopotential of Earth) on the orbital behavior of satellite. In this simulation, the Cowell method for accelerations technique was adopted, the equation of motion with perturbation was solved by 4<sup>th</sup> order Runge-Kutta method with step (1/50000) of period to obtain the state vectors for position and velocity. The results of this simulation have been compared with data that available on TLEs (NORD data in two line elements). The results of state vectors for satellites (Cartosat-2B, Gsat-14 an</p> ... Show More
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Publication Date
Thu Apr 30 2020
Journal Name
Journal Of Economics And Administrative Sciences
Comparison Branch and Bound Algorithm with Penalty Function Method for solving Non-linear Bi-level programming with application
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The problem of Bi-level programming is to reduce or maximize the function of the target by having another target function within the constraints. This problem has received a great deal of attention in the programming community due to the proliferation of applications and the use of evolutionary algorithms in addressing this kind of problem. Two non-linear bi-level programming methods are used in this paper. The goal is to achieve the optimal solution through the simulation method using the Monte Carlo method using different small and large sample sizes. The research reached the Branch Bound algorithm was preferred in solving the problem of non-linear two-level programming this is because the results were better.

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Publication Date
Sun Dec 01 2013
Journal Name
Journal Of Economics And Administrative Sciences
CALCULATION BIASES FOR COEFFICIENTS AND SCALE PARAMETER FOR LINEAR (TYPE 1) EXTREME VALUE REGRESSION MODEL FOR LARGEST VALUES
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Abstract

Characterized by the Ordinary Least Squares (OLS) on Maximum Likelihood for the greatest possible way that the exact moments are known , which means that it can be found, while the other method they are unknown, but approximations to their biases correct to 0(n-1) can be obtained by standard methods. In our research expressions for approximations to the biases of the ML estimators (the regression coefficients and scale parameter) for linear (type 1) Extreme Value Regression Model for Largest Values are presented by using the advanced approach depends on finding the first derivative, second and third.

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Publication Date
Mon Oct 16 2023
Journal Name
Nano And Medical Materials
Preparation and analysis of silver Nanoparticles (Ag Nps) by plant extract techniques of green tea and study optical and structural properties
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Aqueous root extract has been used to examine the green production of silver nanoparticles (AgNPs) by reducing the Ag+ ions in a silver nitrate solution. UV-Vis spectroscopy, X-ray diffraction, field emission scanning electron microscopy, and Fourier transform infrared spectroscopy (FTIR) were used to analyze the produced AgNPs. The AgNPs that were created had a maximum absorbance at 416 nm, were spherical in form, polydispersed in nature, and were 685 nm in size.The AgNPs demonstrated antibacterial efficacy against Escherichia coli and Staphylococcus. The dengue vector Aedes aegypti's second instar larvae were very susceptible to the AgNPs' powerful larvicidal action.

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