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Comparison of some methods for estimating the parameters of the binary logistic regression model using the genetic algorithm with practical application
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Abstract

   Suffering the human because of pressure normal life of exposure to several types of heart disease as a result of due to different factors. Therefore, and in order to find out the case of a death whether or not, are to be modeled using binary logistic regression model

    In this research used, one of the most important models of nonlinear regression models extensive use in the modeling of applications statistical, in terms of heart disease which is the binary logistic regression model. and then estimating the parameters of this model using the statistical estimation methods, another problem will be appears in estimating its parameters, as well as when the number parameters , and to find estimate the parameters using the numerical methods, sometimes does not give optimum solution because it depends on the initial estimators.

   Some standard methods have been proposed and employed after modifying them by using the genetic algorithm approach in estimation to suit the estimation of  the parameters of this of nonlinear regression models, and then making a comparison between two types of the important estimation methods including the standard estimation methods which included the maximum likelihood method, minimum chi-square method, and improved estimation methods developed which by the researcher which included genetic algorithm method depending on the technique estimates , genetic algorithm method depending on the technique estimates , to choose the best method of estimation by default values to estimate parameter multi-linear regression model a method ols and then convert values the real to standardized and different samples sizes during simulation and by using the statistical criteria Mean Squares Error (MSE) for estimators.

    The method is found to be the best one in the first place one among the standard estimation methods, and  method is the best among the important estimation methods for the purpose of estimating the parameters for binary logistic regression model because it has less (MSE) for estimators compared to other methods.

    In the practical side of this study, this model has been used for modeling the own data infected heart disease and estimating the parameters using the method, reached in it by comparing reasons for cases of occurrence death the real with reasons for cases of occurrence death for the estimated to the appropriate model in the modeling of this type of data and extraction the main cause of death is smoking and also the accuracy of the  method in estimating the parameters of the model.

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Publication Date
Thu Dec 12 2013
Journal Name
Iraqi Journal Of Science
Determination of Optimum Mechanical Drilling Parameters for an Iraqi Field with Regression Model
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Publication Date
Sun Oct 23 2022
Journal Name
Baghdad Science Journal
Comparison Between Deterministic and Stochastic Model for Interaction (COVID-19) With Host Cells in Humans
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In this paper, the deterministic and the stochastic models are proposed to study the interaction of the Coronavirus (COVID-19) with host cells inside the human body. In the deterministic model, the value of the basic reproduction number   determines the persistence or extinction of the COVID-19. If   , one infected cell will transmit the virus to less than one cell, as a result,  the person carrying the Coronavirus will get rid of the disease .If   the infected cell  will be able to infect  all  cells that contain ACE receptors. The stochastic model proves that if  are sufficiently large then maybe  give  us ultimate disease extinction although ,  and this  facts also proved by computer simulation.

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Publication Date
Sat Dec 31 2022
Journal Name
Journal Of Economics And Administrative Sciences
Estimation of Causal Effect of treatment via Fuzzy Regression Discontinuity Designs
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In some cases, researchers need to know the causal effect of the treatment in order to know the extent of the effect of the treatment on the sample in order to continue to give the treatment or stop the treatment because it is of no use. The local weighted least squares method was used to estimate the parameters of the fuzzy regression discontinuous model, and the local polynomial method was used to estimate the bandwidth. Data were generated with sample sizes (75,100,125,150 ) in repetition 1000. An experiment was conducted at the Innovation Institute for remedial lessons in 2021 for 72 students participating in the institute and data collection. Those who used the treatment had an increase in their score after

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Publication Date
Thu Jun 01 2023
Journal Name
Baghdad Science Journal
Green synthesis of nano binary oxide SiO2/V2O5 NPs integrated ointment cream application on wound dressings and skin cancer cells
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Green synthesis is depending on preparation of nano composited SiO2/V2O5 by using the modified sol-gel method depending on rice husk ash as a source for the extraction of silica gel and the product powder of nano composited SiO2/V2O5 characterization by many techniques such as X-ray diffraction spectroscopy (XRD), field emission scanning electron microscopy (FESEM), and N2 adsorptions/desorption isotherms (BET). This study also includs the biological effectiveness of SiO2/V2O5 and its effect on inhibiting bacterial growth after the prepared nanomaterial was applied to wound dressings, which gave a promising result for its use as

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Publication Date
Sun Feb 25 2024
Journal Name
Baghdad Science Journal
Optimizing Blockchain Consensus: Incorporating Trust Value in the Practical Byzantine Fault Tolerance Algorithm with Boneh-Lynn-Shacham Aggregate Signature
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The consensus algorithm is the core mechanism of blockchain and is used to ensure data consistency among blockchain nodes. The PBFT consensus algorithm is widely used in alliance chains because it is resistant to Byzantine errors. However, the present PBFT (Practical Byzantine Fault Tolerance) still has issues with master node selection that is random and complicated communication. The IBFT consensus technique, which is enhanced, is proposed in this study and is based on node trust value and BLS (Boneh-Lynn-Shacham) aggregate signature. In IBFT, multi-level indicators are used to calculate the trust value of each node, and some nodes are selected to take part in network consensus as a result of this calculation. The master node is chosen

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Publication Date
Sun May 11 2025
Journal Name
Iraqi Statisticians Journal
Estimating General Linear Regression Model of Big Data by Using Multiple Test Technique
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Publication Date
Sun Mar 01 2015
Journal Name
Journal Of Engineering
Multi-Sites Multi-Variables Forecasting Model for Hydrological Data using Genetic Algorithm Modeling
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A two time step stochastic multi-variables multi-sites hydrological data forecasting model was developed and verified using a case study. The philosophy of this model is to use the cross-variables correlations, cross-sites correlations and the two steps time lag correlations simultaneously, for estimating the parameters of the model which then are modified using the mutation process of the genetic algorithm optimization model. The objective function that to be minimized is the Akiake test value. The case study is of four variables and three sites. The variables are the monthly air temperature, humidity, precipitation, and evaporation; the sites are Sulaimania, Chwarta, and Penjwin, which are located north Iraq. The model performance was

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Publication Date
Wed Mar 10 2021
Journal Name
Baghdad Science Journal
A Comparison Between the Theoretical Cross Section Based on the Partial Level Density Formulae Calculated by the Exciton Model with the Experimental Data for (_79^197)Au nucleus
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In this paper, the theoretical cross section in pre-equilibrium nuclear reaction has been studied for the reaction  at energy 22.4 MeV. Ericson’s formula of partial level density PLD and their corrections (William’s correction and spin correction) have been substituted  in the theoretical cross section and compared with the experimental data for  nucleus. It has been found that the theoretical cross section with one-component PLD from Ericson’s formula when  doesn’t agree with the experimental value and when . There is little agreement only at the high value of energy range with  the experimental cross section. The theoretical cross section that depends on the one-component William's formula and on-component corrected to spi

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Publication Date
Sun Jan 14 2024
Journal Name
Journal Of Al-rafidain University College For Sciences ( Print Issn: 1681-6870 ,online Issn: 2790-2293 )
Using Nonparametric Procedure to Develop an OCMT Estimator for Big Data Linear Regression Model with Application Chemical Pollution in the Tigris River
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Chemical pollution is a very important issue that people suffer from and it often affects the nature of health of society and the future of the health of future generations. Consequently, it must be considered in order to discover suitable models and find descriptions to predict the performance of it in the forthcoming years. Chemical pollution data in Iraq take a great scope and manifold sources and kinds, which brands it as Big Data that need to be studied using novel statistical methods. The research object on using Proposed Nonparametric Procedure NP Method to develop an (OCMT) test procedure to estimate parameters of linear regression model with large size of data (Big Data) which comprises many indicators associated with chemi

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Publication Date
Tue Oct 27 2020
Journal Name
Journal Of Mechanics Of Continua And Mathematical Sciences
AUTOMATIC ARABIC KEYWORD EXTRACTION USING LOGISTIC REGRESSION
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