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Fuzzy Stochastic Probability of The Solution of Single Stationary Non- Homogeneous Linear Fuzzy Random Differential Equations
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Publication Date
Mon Aug 01 2016
Journal Name
Journal Of Economics And Administrative Sciences
"Compared some of the semi-parametric methods in analysis of single index model "
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As the process of  estimate for model and variable selection significant is a crucial process in the semi-parametric modeling At the beginning of the modeling process often At there are many explanatory variables to Avoid the loss of any explanatory elements may be important as a result , the selection of significant variables become necessary , so the process of variable selection is not intended to simplifying  model complexity explanation , and also predicting. In this research was to use some of the semi-parametric methods (LASSO-MAVE , MAVE and The proposal method (Adaptive LASSO-MAVE) for variable selection and estimate semi-parametric single index model (SSIM) at the same time .

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Publication Date
Fri Mar 10 2023
Journal Name
Indian Journal Of Physics
Describing the differential inelastic inverse mean free path of PMMA polymer with the Mermin–Belkacem-Sigmund model
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Publication Date
Sun Sep 06 2009
Journal Name
Baghdad Science Journal
Extension of the Chebyshev Method of Quassi-Linear Parabolic P.D.E.S With Mixed Boundary Conditions
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The researcher [1-10] proposed a method for computing the numerical solution to quasi-linear parabolic p.d.e.s using a Chebyshev method. The purpose of this paper is to extend the method to problems with mixed boundary conditions. An error analysis for the linear problem is given and a global element Chebyshev method is described. A comparison of various chebyshev methods is made by applying them to two-point eigenproblems. It is shown by analysis and numerical examples that the approach used to derive the generalized Chebyshev method is comparable, in terms of the accuracy obtained, with existing Chebyshev methods.

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Publication Date
Tue Dec 01 2020
Journal Name
Baghdad Science Journal
A Modified Support Vector Machine Classifiers Using Stochastic Gradient Descent with Application to Leukemia Cancer Type Dataset
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Support vector machines (SVMs) are supervised learning models that analyze data for classification or regression. For classification, SVM is widely used by selecting an optimal hyperplane that separates two classes. SVM has very good accuracy and extremally robust comparing with some other classification methods such as logistics linear regression, random forest, k-nearest neighbor and naïve model. However, working with large datasets can cause many problems such as time-consuming and inefficient results. In this paper, the SVM has been modified by using a stochastic Gradient descent process. The modified method, stochastic gradient descent SVM (SGD-SVM), checked by using two simulation datasets. Since the classification of different ca

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Publication Date
Mon Apr 06 2020
Journal Name
Journal Of Techniques
Finite Element Modeling Of Saint-Venant Equations For Shatt-Al Hilla
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Shatt Al-Hilla was considered one of the important branches of Euphrates River that supplies irrigation water to millions of dunams of planted areas. It is important to control the velocity and water level along the river to maintain the required level for easily diverting water to the branches located along the river. So, in this research, a numerical model was developed to simulate the gradually varied unsteady flow in Shatt AL-Hilla. The present study aims to solve the continuity and momentum (Saint-Venant) equations numerically to predict the hydraulic characteristics in the river using Galerkin finite element method. A computer program was designed and built using the programming language FORTRAN-77. Fifty kilometers was consid

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Publication Date
Thu Mar 01 2007
Journal Name
Al-khwarizmi Engineering Journal
The Inverse Solution Of Dexterous Robot By Using Neural Networks
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The inverse kinematics of redundant manipulators has infinite solutions by using conventional methods, so that, this work presents applicability of intelligent tool (artificial neural network ANN) for finding one desired solution from these solutions. The inverse analysis and trajectory planning of a three link redundant planar robot have been studied in this work using a proposed dual neural networks model (DNNM), which shows a predictable time decreasing in the training session. The effect of the number of the training sets on the DNNM output and the number of NN layers have been studied. Several trajectories have been implemented using point to point trajectory planning algorithm with DNNM and the result shows good accuracy of the end

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Publication Date
Tue Jun 06 2023
Journal Name
Journal Of University Of Anbar For Pure Science (juaps)
Approximate Solution of Emden-Fowler Equation Using the Galerkin Method
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Publication Date
Wed Aug 03 2016
Journal Name
Technology Reports Of Kansai University
Some statistical results for solution type of the Inequalities system
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Publication Date
Mon Dec 30 2002
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
The Optimal Corrosion Inhibition of Aluminum in 0.1M NaCl Solution
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Publication Date
Sun Feb 10 2019
Journal Name
Iraqi Journal Of Physics
The role of atmospheric non-thermal plasma in the bacteria inactivation
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Non-thermal atmospheric pressure plasma has emerged as a
new promising tool in medicine and biology. In this work, A DBD
system was built as a source of atmospheric pressure non-thermal
Plasma suitable for clinical and biological applications. E. coli and
staphylococcus spp bacteria were exposed to the DBD plasma for a
period of time as inactivation (sterilization) process. A series of
experiments were achieved under different operating conditions. The
results showed that the inactivation, of the two kinds of bacteria, was
affected (increasing or decreasing) according to operation conditions
because they affects, as expected, the produced plasma properties
according to those conditions.

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