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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
Wed Jan 01 2020
Journal Name
Journal Of King Saud University - Science
Three iterative methods for solving second order nonlinear ODEs arising in physics
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Publication Date
Mon Apr 26 2021
Journal Name
Journal Of Electrical Engineering & Technology
ANFIS Based Reinforcement Learning Strategy for Control A Nonlinear Coupled Tanks System
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Publication Date
Mon Jun 01 2015
Journal Name
International Photonics And Optoelectronics
Canonical Logic Units using Bidirectional Four-Wave Mixing in Highly Nonlinear Fiber
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All-optical canonical logic units at 40 Gb/s using bidirectional four-wave mixing (FWM) in highly nonlinear fiber are proposed and experimentally demonstrated. Clear temporal waveforms and correct pattern streams are successfully observed in the experiment. This scheme can reduce the amount of nonlinear devices and enlarge the computing capacity compared with general ones. The numerical simulations are made to analyze the relationship between the FWM efficiency and the position of two interactional signals. © 2015 Chinese Laser Press

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Publication Date
Thu Jun 01 2017
Journal Name
Chaos, Solitons & Fractals
A semi-analytical iterative method for solving nonlinear thin film flow problems
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Publication Date
Wed Mar 10 2021
Journal Name
Baghdad Science Journal
Mathematical model of optical amplifier using nonlinear stimulated Brillouin scattering (SBS) in optical fiber
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We demonstrate the results of a mathematical model for investigation the nonlinear Stimulated Brillouin Scattering (SBS), which can be employed to achieve high optical amplifier. The SBS is created by interaction between the incident We demonstrate the results of a mathematical model for investigation the nonlinear Stimulated Brillouin Scattering (SBS), which can be employed to achieve high optical amplifier. The SBS is created by interaction between the incident light and the acoustic vibration fiber. The design criteria and the amplification characteristic of the Brillouin amplifier is demonstrated and discussed for fiber Brillouin amplifier using different pump power with different fiber length. The results show, high Brillouin gain can

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Publication Date
Sun Sep 01 2019
Journal Name
Baghdad Science Journal
An Analysis of a Partial Temporary Immunity SIR Epidemic Model with Nonlinear Treatment Rate
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     A partial temporary immunity SIR epidemic model involv nonlinear treatment rate is proposed and studied. The basic reproduction number  is determined. The local and global stability of all equilibria of the model are analyzed. The conditions for occurrence of local bifurcation in the proposed epidemic model are established. Finally, numerical simulation is used to confirm our obtained analytical results and specify the control set of parameters that affect the dynamics of the model.

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Publication Date
Sun Jun 01 2014
Journal Name
Baghdad Science Journal
Solution of Nonlinear High Order Multi-Point Boundary Value Problems By Semi-Analytic Technique
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In this paper, we present new algorithm for the solution of the nonlinear high order multi-point boundary value problem with suitable multi boundary conditions. The algorithm is based on the semi-analytic technique and the solutions are calculated in the form of a rapid convergent series. It is observed that the method gives more realistic series solution that converges very rapidly in physical problems. Illustrative examples are provided to demonstrate the efficiency and simplicity of the proposed method in solving this type of multi- point boundary value problems.

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Publication Date
Thu Oct 20 2016
Journal Name
Sociological Methods & Research
Mean Monte Carlo Finite Difference Method for Random Sampling of a Nonlinear Epidemic System
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In this article, a numerical method integrated with statistical data simulation technique is introduced to solve a nonlinear system of ordinary differential equations with multiple random variable coefficients. The utilization of Monte Carlo simulation with central divided difference formula of finite difference (FD) method is repeated n times to simulate values of the variable coefficients as random sampling instead being limited as real values with respect to time. The mean of the n final solutions via this integrated technique, named in short as mean Monte Carlo finite difference (MMCFD) method, represents the final solution of the system. This method is proposed for the first time to calculate the numerical solution obtained fo

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Publication Date
Thu Feb 01 2024
Journal Name
Journal Of Engineering
Predicting Biochemical Oxygen Demand at the Inlet of Al-Rustumiya Wastewater Treatment Plant Using Different Mathematical Techniques
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Water quality planning relies on Biochemical Oxygen Demand BOD. BOD testing takes five days. The Particle Swarm Optimization (PSO) is increasingly used for water resource forecasting. This work designed a PSO technique for estimating everyday BOD at Al-Rustumiya wastewater treatment facility inlet. Al-Rustumiya wastewater treatment plant provided 702 plant-scale data sets during 2012-2022. The PSO model uses the daily data of the water quality parameters, including chemical oxygen demand (COD), chloride (Cl-), suspended solid (SS), total dissolved solids (TDS), and pH, to determine how each variable affects the daily incoming BOD. PSO and multiple linear regression (MLR) findings are compared, and their perfor

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Publication Date
Sat Sep 04 2021
Journal Name
Neuroquantology
Nanotechnology and the Most Important Characterization Techniques for Nanomaterial's: A Review
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Due to the importance of nanotechnology because of its features and applications in various fields, it has become the focus of attention of the world and researchers. In this study, the concept of nanotechnology and nanomaterials was identified, the most important methods of preparing them, as well as the preparation techniques and the most important devices used in their characterization.

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