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Comparison of classical method and optimization methods for estimating parameters in nonlinear ordinary differential equation
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  This study is concerned with the estimation of constant  and time-varying parameters in non-linear ordinary differential equations, which do not have analytical solutions. The estimation is done in a multi-stage method where constant and time-varying parameters are estimated in a straight sequential way from several stages. In the first stage, the model of the differential equations is converted to a regression model that includes the state variables with their derivatives and then the estimation of the state variables and their derivatives in a penalized splines method and compensating the estimations in the regression model. In the second stage, the pseudo- least squares method was used to estimate the constant parameters. In the third stage, the remaining constant parameters and the time-varying parameters are estimated by using a semi-parametric regression model. This method is compared with the optimization method, which depends on the algorithm of differential evolution algorithm to estimate unknown parameters. The comparison was made using simulations. The results showed that the results were better to the method based on the differential evolution algorithm.

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Publication Date
Fri Nov 01 2013
Journal Name
Al-nahrain Journal Of Science
Modified third order iterative method for solving nonlinear equations
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Many numerical approaches have been suggested to solve nonlinear problems. In this paper, we suggest a new two-step iterative method for solving nonlinear equations. This iterative method has cubic convergence. Several numerical examples to illustrate the efficiency of this method by Comparison with other similar methods is given.

Publication Date
Sat May 01 2021
Journal Name
Journal Of Physics: Conference Series
Runge-kutta Numerical Method for Solving Nonlinear Influenza Model
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Abstract<p>The main object of this study is to solve a system of nonlinear ordinary differential equations (ODE) of the first order governing the epidemic model using numerical methods. The application under study is a mathematical epidemic model which is the influenza model at Australia in 1919. Runge-kutta methods of order 4 and of order 45 for solving this initial value problem(IVP) problem have been used. Finally, the results obtained have been discussed tabularly and graphically.</p>
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Publication Date
Tue Dec 26 2017
Journal Name
Al-khwarizmi Engineering Journal
Optimization of Wear Parameters in AISI 4340 Steel
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 This study investigated the optimization of wear behavior of AISI 4340 steel based on the Taguchi method under various testing conditions. In this paper, a neural network and the Taguchi design method have been implemented for minimizing the wear rate in 4340 steel. A back-propagation neural network (BPNN) was developed to predict the wear rate. In the development of a predictive model, wear parameters like sliding speed, applying load and sliding distance were considered as the input model variables of the AISI 4340 steel. An analysis of variance (ANOVA) was used to determine the significant parameter affecting the wear rate. Finally, the Taguchi approach was applied to determine

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Publication Date
Mon Mar 11 2019
Journal Name
Baghdad Science Journal
Study the Effect of Cold Plasma on the Nonlinear Properties of Polymeric Membranes Rod Amine (R3Go)
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The nonlinear optical properties for polymeric (PMMA) doping with dye Rhodmine (R3Go) has been studied .The samples are prepared by normal polymerization method with concentrations of 5x10-5mol/l and a thickness of 272.5µm.

                         Plasma effect was studied on samples prepared before and after exposure to the Nd: YAG laser for three times 5, 10 and 15 minutes. Z-Scan technique is used to determine the nonlinear optical properties such as; refractive index (n2) and the coefficient of nonlinear absorption (β). It was found that the nonlinear properties is change by increasi

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Publication Date
Tue Jun 20 2023
Journal Name
Baghdad Science Journal
Comparison between Modified Weighted Pareto Distribution and Many other Distributions
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In 2020 one of the researchers in this paper, in his first research, tried to find out the Modified Weighted Pareto Distribution of Type I by using the Azzalini method for weighted distributions, which contain three parameters, two of them for scale while the third for shape.This research compared the distribution with two other distributions from the same family; the Standard Pareto Distribution of Type I and the Generalized Pareto Distribution by using the Maximum likelihood estimator which was derived by the researchers for Modified Weighted Pareto Distribution of Type I, then the Mont Carlo method was used–that is one of the simulation manners for generating random samples data in different sizes ( n= 10,30,50), and in di

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Publication Date
Sun Mar 01 2015
Journal Name
Computer Systems Science & Engineering
Parameters' fine tuning of differential evolution algorithm
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Most heuristic search method's performances are dependent on parameter choices. These parameter settings govern how new candidate solutions are generated and then applied by the algorithm. They essentially play a key role in determining the quality of the solution obtained and the efficiency of the search. Their fine-tuning techniques are still an on-going research area. Differential Evolution (DE) algorithm is a very powerful optimization method and has become popular in many fields. Based on the prolonged research work on DE, it is now arguably one of the most outstanding stochastic optimization algorithms for real-parameter optimization. One reason for its popularity is its widely appreciated property of having only a small number of par

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Publication Date
Fri Jan 01 2016
Journal Name
Results In Physics
An efficient iterative method for solving the Fokker–Planck equation
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Publication Date
Tue Jun 30 2020
Journal Name
Journal Of Economics And Administrative Sciences
Comparison Between Partial Least Square Regression(PLSR) and Tree Regression by Using Simulation(RT).
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This research discussed, the process of comparison between the regression model of partial least squares and tree regression, where these models included two types of statistical methods represented by the first type "parameter statistics" of the partial least squares, which is adopted when the number of variables is greater than the number of observations and also when the number of observations larger than the number of variables, the second type is the "nonparametric statistic" represented by tree regression, which is the division of data in a hierarchical way. The regression models for the two models were estimated, and then the comparison between them, where the comparison between these methods was according to a Mean Square

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Publication Date
Sun Nov 01 2020
Journal Name
Iraqi Journal Of Laser
A Comparison between Er,Cr:YSGG 2780 nm Laser and Carbide Fissure Bur in Root-End resection
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Aim: The Aim of the study is to compare between Er,Cr:YSGG 2780 nm laser and carbide fissure bur in root-end resection regarding the morphological variations, temperature changes and the duration of resection process.

Settings and Design: 5 W, 25 Hz, 50% water, 80% air,25.47 J/cm2 .

Material and method: twenty-one extracted single rooted teeth endodontically were treated, twenty teeth were obturated and divided into two groups according to method of resection. Group 1 root-end resected using cross cut carbide bur while group 2 root-end resected using laser with MGG6 sapphire tip of 600 μm diameter. Temperature on external root surface and duration of resection were recor

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Publication Date
Wed Feb 01 2017
Journal Name
Journal Of Economics And Administrative Sciences
A comparison between the logistic regression model and Linear Discriminant analysis using Principal Component unemployment data for the province of Baghdad
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     The objective of the study is to demonstrate the predictive ability is better between the logistic regression model and Linear Discriminant function using the original data first and then the Home vehicles to reduce the dimensions of the variables for data and socio-economic survey of the family to the province of Baghdad in 2012 and included a sample of 615 observation with 13 variable, 12 of them is an explanatory variable and the depended variable is number of workers and the unemployed.

     Was conducted to compare the two methods above and it became clear by comparing the  logistic regression model best of a Linear Discriminant  function written

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