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Effective Computational Methods for Solving the Jeffery-Hamel Flow Problem

In this paper, the effective computational method (ECM) based on the standard monomial polynomial has been implemented to solve the nonlinear Jeffery-Hamel flow problem. Moreover, novel effective computational methods have been developed and suggested in this study by suitable base functions, namely Chebyshev, Bernstein, Legendre, and Hermite polynomials. The utilization of the base functions converts the nonlinear problem to a nonlinear algebraic system of equations, which is then resolved using the Mathematica®12 program. The development of effective computational methods (D-ECM) has been applied to solve the nonlinear Jeffery-Hamel flow problem, then a comparison between the methods has been shown. Furthermore, the maximum error remainder ( ) has been calculated to exhibit the reliability of the suggested methods. The results persuasively prove that ECM and D-ECM are accurate, effective, and reliable in getting approximate solutions to the problem.

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Publication Date
Tue Sep 08 2020
Journal Name
Baghdad Science Journal
A comparison among Different Methods for Estimating Regression Parameters with Autocorrelation Problem under Exponentially Distributed Error

Multiple linear regressions are concerned with studying and analyzing the relationship between the dependent variable and a set of explanatory variables. From this relationship the values of variables are predicted. In this paper the multiple linear regression model and three covariates were studied in the presence of the problem of auto-correlation of errors when the random error distributed the distribution of exponential. Three methods were compared (general least squares, M robust, and Laplace robust method). We have employed the simulation studies and calculated the statistical standard mean squares error with sample sizes (15, 30, 60, 100). Further we applied the best method on the real experiment data representing the varieties of

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Publication Date
Mon Jan 01 2007
Journal Name
Iraqi Journal Of Science
Adaptive methods for matching problem

In this paper, we deal with the problem of general matching of two images one of them has experienced geometrical transformations, to find the correspondence between two images. We develop the invariant moments for traditional techniques (moments of inertia) with new approach to enhance the performance for these methods. We test various projections directional moments, to extract the difference between Block Distance Moment (BDM) and evaluate their reliability. Three adaptive strategies are shown for projections directional moments, that are raster (vertical and horizontal) projection, Fan-Bean projection and new projection procedure that is the square projection method. Our paper started with the description of a new algorithm that is low

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Publication Date
Wed Feb 01 2023
Journal Name
Baghdad Science Journal
Efficient Approach for Solving (2+1) D- Differential Equations

     In this article, a new efficient approach is presented to solve a type of partial differential equations, such (2+1)-dimensional differential equations non-linear, and nonhomogeneous. The procedure of the new approach is suggested to solve important types of differential equations and get accurate analytic solutions i.e., exact solutions. The effectiveness of the suggested approach based on its properties compared with other approaches has been used to solve this type of differential equations such as the Adomain decomposition method, homotopy perturbation method, homotopy analysis method, and variation iteration method. The advantage of the present method has been illustrated by some examples.

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Publication Date
Fri Dec 30 2022
Journal Name
Iraqi Journal Of Science
The Operational Matrices Methods for Solving Falkner-Skan Equations

     The method of operational matrices is based on the Bernoulli and Shifted Legendre polynomials which is used to solve the Falkner-Skan equation. The nonlinear differential equation converting to a system of nonlinear equations is solved using Mathematica®12, and the approximate solutions are obtained. The efficiency of these methods was studied by calculating the maximum error remainder ( ), and it was found that their efficiency increases as  increases. Moreover, the obtained approximate solutions are compared with the numerical solution obtained by the fourth-order Runge-Kutta method (RK4), which gives  a good agreement.

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Publication Date
Sat Dec 01 2018
Journal Name
Journal Of Economics And Administrative Sciences
Compare Estimate Methods of Parameter to Scheffʼe Mixture Model By Using Generalized Inverse and The Stepwise Regression procedure for Treatment Multicollinearity Problem

Mixture experiments are response variables based on the proportions of component for this mixture. In our research we will compare the scheffʼe model with the kronecker model for the mixture experiments, especially when the experimental area is restricted.

     Because of the experience of the mixture of high correlation problem and the problem of multicollinearity between the explanatory variables, which has an effect on the calculation of the Fisher information matrix of the regression model.

     to estimate the parameters of the mixture model, we used the (generalized inverse ) And the Stepwise Regression procedure

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Publication Date
Sat Oct 28 2023
Journal Name
Baghdad Science Journal
Newton-Kantorovich Method for Solving One of the Non-Linear Sturm-Liouville Problems

Due to its importance in physics and applied mathematics, the non-linear Sturm-Liouville problems
witnessed massive attention since 1960. A powerful Mathematical technique called the Newton-Kantorovich
method is applied in this work to one of the non-linear Sturm-Liouville problems. To the best of the authors’
knowledge, this technique of Newton-Kantorovich has never been applied before to solve the non-linear
Sturm-Liouville problems under consideration. Accordingly, the purpose of this work is to show that this
important specific kind of non-linear Sturm-Liouville differential equations problems can be solved by
applying the well-known Newton-Kantorovich method. Also, to show the efficiency of appl

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Publication Date
Tue Sep 08 2020
Journal Name
Baghdad Science Journal
A Proposed Analytical Method for Solving Fuzzy Linear Initial Value Problems

     In this article, we aim to define a universal set consisting of the subscripts of the fuzzy differential equation (5) except the two elements  and , subsets of that universal set are defined according to certain conditions. Then, we use the constructed universal set with its subsets for suggesting an analytical method which facilitates solving fuzzy initial value problems of any order by using the strongly generalized H-differentiability. Also, valid sets with graphs for solutions of fuzzy initial value problems of higher orders are found.

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Publication Date
Mon Sep 23 2019
Journal Name
Baghdad Science Journal
New Approach for Solving Three Dimensional Space Partial Differential Equation

This paper presents a new transform method to solve partial differential equations, for finding suitable accurate solutions in a wider domain. It can be used to solve the problems without resorting to the frequency domain. The new transform is combined with the homotopy perturbation method in order to solve three dimensional second order partial differential equations with initial condition, and the convergence of the solution to the exact form is proved. The implementation of the suggested method demonstrates the usefulness in finding exact solutions. The practical implications show the effectiveness of approach and it is easily implemented in finding exact solutions.

       Finally, all algori

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Publication Date
Mon Feb 01 2021
Journal Name
Journal Of Physics: Conference Series
Bayesian Computational Methods of the Logistic Regression Model
Abstract<p>In this paper, we will discuss the performance of Bayesian computational approaches for estimating the parameters of a Logistic Regression model. Markov Chain Monte Carlo (MCMC) algorithms was the base estimation procedure. We present two algorithms: Random Walk Metropolis (RWM) and Hamiltonian Monte Carlo (HMC). We also applied these approaches to a real data set.</p>
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Publication Date
Sat Feb 26 2022
Journal Name
Iraqi Journal Of Science
New Class of Rank 1 Update for Solving Unconstrained Optimization Problem: New Class of Rank 1 Update for solving Unconstrained Optimization Problem

     The focus of this article is to add a new class of rank one of  modified Quasi-Newton techniques to solve the problem of unconstrained optimization by updating the inverse Hessian matrix with an update of rank 1, where a diagonal matrix is the first component of the next inverse Hessian approximation, The inverse Hessian matrix is  generated by the method proposed which is symmetric and it satisfies the condition of modified quasi-Newton, so the global convergence is retained. In addition, it is positive definite that  guarantees the existence of the minimizer at every iteration of the objective function. We use  the program MATLAB to solve an algorithm function to introduce the feasibility of

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