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Estimation parameter for non-linear regression by using HGSABAT algorithm
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This study offers a new Mixed Meta Heuristics algorithm (HGSABAT) for estimating the parameter values of each of the six categories of Non-Linear regression models examined (Misrald, Meyer4, Meyer7, Militky4, Militky2, and MGH09) by combining the Gravitational Search Algorithm and Bat Algorithm. Some models have different numbers of parameters. For example, the Misrald and Militky2 models of the Non-Linear Regression model have two parameters (Bl, B2). In contrast, the MGH09 and Militky4 models have four parameters (MGHl, MGH2, MGH3, and MGH4), in which location as the Meyer4 and Meyer7 models have three attributes (Meyerl, MGH2, and MGH3). To examine the effectiveness of the suggested Hybrid Meta Heuristics algorithm (HGSABAT), a simulation study based on Mean Square Error criteria is employed. Furthermore, using three metaheuristic algorithms, the simulation results are compared using Practical Swarm Enhancement, Gravitational Search, and BAT. The numerical results will be obtained using the Matlab program version 2020. Because the hybrid algorithm (HGSABAT) has a lower mean error than one of the other techniques, the mean error in the squares estimation techniques that were taken into consideration, the results demonstrated that it is satisfactory for parameter

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Publication Date
Wed Mar 18 2020
Journal Name
Baghdad Science Journal
Solving Linear Volterra – Fredholm Integral Equation of the Second Type Using Linear Programming Method
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In this paper, a new technique is offered for solving three types of linear integral equations of the 2nd kind including Volterra-Fredholm integral equations (LVFIE) (as a general case), Volterra integral equations (LVIE) and Fredholm integral equations (LFIE) (as special cases). The new technique depends on approximating the solution to a polynomial of degree and therefore reducing the problem to a linear programming problem(LPP), which will be solved to find the approximate solution of LVFIE. Moreover, quadrature methods including trapezoidal rule (TR), Simpson 1/3 rule (SR), Boole rule (BR), and Romberg integration formula (RI) are used to approximate the integrals that exist in LVFIE. Also, a comparison between those methods is

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Publication Date
Thu Jan 16 2020
Journal Name
Periodicals Of Engineering And Natural Sciences
Comparison of some reliability estimation methods for Laplace distribution using simulations
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In this paper, we derived an estimator of reliability function for Laplace distribution with two parameters using Bayes method with square error loss function, Jeffery’s formula and conditional probability random variable of observation. The main objective of this study is to find the efficiency of the derived Bayesian estimator compared to the maximum likelihood of this function and moment method using simulation technique by Monte Carlo method under different Laplace distribution parameters and sample sizes. The consequences have shown that Bayes estimator has been more efficient than the maximum likelihood estimator and moment estimator in all samples sizes

Publication Date
Wed Feb 01 2023
Journal Name
International Journal Of Revolution In Science And Humanity
Nonparametric Estimation of Failure Periods for Log Normal Distribution Using Bootstra
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A non-parametric kernel method with Bootstrap technology was used to estimate the confidence intervals of the system failure function of the log-normal distribution trace data. These are the times of failure of the machines of the spinning department of the weaving company in Wasit Governorate. Estimating the failure function in a parametric way represented by the method of the maximum likelihood estimator (MLE). The comparison between the parametric and non-parametric methods was done by using the average of Squares Error (MES) criterion. It has been noted the efficiency of the nonparametric methods based on Bootstrap compared to the parametric method. It was also noted that the curve estimation is more realistic and appropriate for the re

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Publication Date
Sun Aug 30 2020
Journal Name
Periodicals Of Engineering And Natural Sciences (pen)
Kernel estimation of returns of retirement funds of employers based on monetary earnings (subscriptions and compensation) via regression discontinuity in Iraq
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Regression Discontinuity (RD) means a study that exposes a definite group to the effect of a treatment. The uniqueness of this design lies in classifying the study population into two groups based on a specific threshold limit or regression point, and this point is determined in advance according to the terms of the study and its requirements. Thus , thinking was focused on finding a solution to the issue of workers retirement and trying to propose a scenario to attract the idea of granting an end-of-service reward to fill the gap ( discontinuity point) if it had not been granted. The regression discontinuity method has been used to study and to estimate the effect of the end -service reward on the cutoff of insured workers as well as t

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Publication Date
Sat Dec 31 2016
Journal Name
Al-kindy College Medical Journal
Non Traumatic Hip Osteonecrosis Treated By Non Vascularised Bone Graft Versus Core Decompression
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Background: Avascular necrosis (AVN) is defined as cellular death of bone components due to interruption of the blood supply; the bone structures then collapse, resulting in bone destruction, pain, and loss of joint function. AVN is associated with numerous conditions and usually involves the epiphysis of long bones, such as the femoral head. In clinical practice, AVN is most commonly encountered in the hip. Early diagnosis and appropriate intervention can delay the need for joint replacement. However, most patients present late in the disease course. Without treatment, the process is almost always progressive, leading to joint destruction within 5 years.Treatment of a vascular necrosis depends mainly on early diagnosis which mainly base

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Publication Date
Sat Apr 01 2023
Journal Name
Baghdad Science Journal
Honeyword Generation Using a Proposed Discrete Salp Swarm Algorithm
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Honeywords are fake passwords that serve as an accompaniment to the real password, which is called a “sugarword.” The honeyword system is an effective password cracking detection system designed to easily detect password cracking in order to improve the security of hashed passwords. For every user, the password file of the honeyword system will have one real hashed password accompanied by numerous fake hashed passwords. If an intruder steals the password file from the system and successfully cracks the passwords while attempting to log in to users’ accounts, the honeyword system will detect this attempt through the honeychecker. A honeychecker is an auxiliary server that distinguishes the real password from the fake passwords and t

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Publication Date
Tue Oct 22 2024
Journal Name
Iraqi Statisticians Journal
Inferential Methods for the Dagum Regression Model
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The Dagum Regression Model, introduced to address limitations in traditional econometric models, provides enhanced flexibility for analyzing data characterized by heavy tails and asymmetry, which is common in income and wealth distributions. This paper develops and applies the Dagum model, demonstrating its advantages over other distributions such as the Log-Normal and Gamma distributions. The model's parameters are estimated using Maximum Likelihood Estimation (MLE) and the Method of Moments (MoM). A simulation study evaluates both methods' performance across various sample sizes, showing that MoM tends to offer more robust and precise estimates, particularly in small samples. These findings provide valuable insights into the ana

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Publication Date
Sun Jun 01 2008
Journal Name
2008 Ieee International Joint Conference On Neural Networks (ieee World Congress On Computational Intelligence)
Linear block code decoder using neural network
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Publication Date
Thu Jan 01 2015
Journal Name
International Journal Of Computer Science And Mobile Computing
Image Compression using Hierarchal Linear Polynomial Coding
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Publication Date
Wed Jul 01 2015
Journal Name
Journal Of Engineering
Optimal Location of Static Synchronous Compensator (STATCOM) for IEEE 5-Bus Standard System Using Genetic Algorithm
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Heuristic approaches are traditionally applied to find the optimal size and optimal location of Flexible AC Transmission Systems (FACTS) devices in power systems. Genetic Algorithm (GA) technique has been applied to solve power engineering optimization problems giving better results than classical methods. This paper shows the application of GA for optimal sizing and allocation of a Static Compensator (STATCOM) in a power system. STATCOM devices used to increase transmission systems capacity and enhance voltage stability by regulate the voltages at its terminal by controlling the amount of reactive power injected into or absorbed from the power system. IEEE 5-bus standard system is used as an example to illustrate the te

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