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Estimate the Nonparametric Regression Function Using Canonical Kernel
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    This research aims to review the importance of estimating the nonparametric regression function using so-called Canonical Kernel which depends on re-scale the smoothing parameter, which has a large and important role in Kernel  and give the sound amount of smoothing .

We has been shown the importance of this method through the application of these concepts on real data refer to international exchange rates to the U.S. dollar against the Japanese yen for the period from January 2007 to March 2010. The results demonstrated preference the nonparametric estimator with Gaussian on the other nonparametric and parametric regression estimators (Simple and Multiple linear regressions).

 

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Publication Date
Mon Jun 01 2015
Journal Name
International Photonics And Optoelectronics
Canonical Logic Units using Bidirectional Four-Wave Mixing in Highly Nonlinear Fiber
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All-optical canonical logic units at 40 Gb/s using bidirectional four-wave mixing (FWM) in highly nonlinear fiber are proposed and experimentally demonstrated. Clear temporal waveforms and correct pattern streams are successfully observed in the experiment. This scheme can reduce the amount of nonlinear devices and enlarge the computing capacity compared with general ones. The numerical simulations are made to analyze the relationship between the FWM efficiency and the position of two interactional signals. © 2015 Chinese Laser Press

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Publication Date
Wed Mar 01 2023
Journal Name
Baghdad Science Journal
Momentum Ranking Function of Z-Numbers and its Application to Game Theory
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After Zadeh introduced the concept of z-number scientists in various fields have shown keen interest in applying this concept in various applications. In applications of z-numbers, to compare two z-numbers, a ranking procedure is essential.  While a few ranking functions have been already proposed in the literature there is a need to evolve some more good ranking functions.  In this paper, a novel ranking function for z-numbers is proposed- "the Momentum Ranking Function"(MRF). Also, game theoretic problems where the payoff matrix elements are z-numbers are considered and the application of the momentum ranking function in such problems is demonstrated.

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Publication Date
Tue Jan 29 2019
Journal Name
Journal Of The College Of Education For Women
Compared to Estimate the volume of runoff Basins valley Dwiridj my way (SCS-CN), (GIUH) using (GIS)
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The valley Dwiridj of drainage basins task that lies east of Iraq and thus we have in this study the application of tow models athletes on the three basins of the valley to get Mor e values accurate to Estimate the volume of runoff and peak discharge and time climax and through the use of Technology remote sensing (GIS),has been show through the application of both models, that the maximum value for the amount of Dwiridj valley of (1052/m3/s) According to Equation (SCS-CN) and about (1370.2/m3/s)by approach (GIUH) that difference is the amount of discharge to the Equation (SCS-CN) ar not accurate as(GIUH) approaches Equation ecalling the results of the Field ces Department of damand reservoirs that the volume of runoff to the valley wase

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Publication Date
Thu Dec 01 2016
Journal Name
Journal Of Economics And Administrative Sciences
solving linear fractional programming problems (LFP) by Using denominator function restriction method and compare it with linear transformations method
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Abstract

The use of modern scientific methods and techniques, is considered important topics to solve many of the problems which face some sector, including industrial, service and health. The researcher always intends to use modern methods characterized by accuracy, clarity and speed to reach the optimal solution and be easy at the same time in terms of understanding and application.

the research presented this comparison between the two methods of solution for linear fractional programming models which are linear transformation for Charnas & Cooper , and denominator function restriction method through applied on the oil heaters and gas cookers plant , where the show after reac

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Publication Date
Fri Sep 30 2022
Journal Name
Journal Of Economics And Administrative Sciences
Semi Parametric Logistic Regression Model with the Outputs Representing Trapezoidal Intuitionistic Fuzzy Number
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In this paper, the fuzzy logic and the trapezoidal fuzzy intuitionistic number were presented, as well as some properties of the trapezoidal fuzzy intuitionistic number and semi- parametric logistic regression model when using the trapezoidal fuzzy intuitionistic number. The output variable represents the dependent variable sometimes cannot be determined in only two cases (response, non-response)or (success, failure) and more than two responses, especially in medical studies; therefore so, use a semi parametric logistic regression model with the output variable (dependent variable) representing a trapezoidal fuzzy intuitionistic number.

the model was estimated on simulati

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Publication Date
Wed Aug 01 2018
Journal Name
Journal Of Economics And Administrative Sciences
Compare to the conditional logistic regression models with fixed and mixed effects for longitudinal data
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Mixed-effects conditional logistic regression is evidently more effective in the study of qualitative differences in longitudinal pollution data as well as their implications on heterogeneous subgroups. This study seeks that conditional logistic regression is a robust evaluation method for environmental studies, thru the analysis of environment pollution as a function of oil production and environmental factors. Consequently, it has been established theoretically that the primary objective of model selection in this research is to identify the candidate model that is optimal for the conditional design. The candidate model should achieve generalizability, goodness-of-fit, parsimony and establish equilibrium between bias and variab

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Publication Date
Sat Feb 01 2014
Journal Name
Journal Of Economics And Administrative Sciences
Comparison of some robust methods to estimate parameters of partial least squares regression (PLSR)
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   The technology of reducing dimensions and choosing variables are very important topics in statistical analysis to multivariate. When two or more of the predictor variables are linked in the complete or incomplete regression relationships, a problem of multicollinearity are occurred which consist of the breach of one basic assumptions of the ordinary least squares method with incorrect estimates results.

 There are several methods proposed to address this problem, including the partial least squares (PLS), used to reduce dimensional regression analysis. By using linear transformations that convert a set of variables associated with a high link to a set of new independent variables and unr

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Publication Date
Sun Aug 30 2020
Journal Name
Journal Of Economics And Administrative Sciences
Comparison of the performance of some r- (k,d) class estimators with the (PCTP) estimator that used in estimating the general linear regression model in the presence of autocorrelation and multicollinearity problems at the same time "
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In the analysis of multiple linear regression, the problem of multicollinearity and auto-correlation drew the attention of many researchers, and given the appearance of these two problems together and their bad effect on the estimation, some of the researchers found new methods to address these two problems together at the same time. In this research a comparison for the performance of the Principal Components Two Parameter estimator (PCTP) and The (r-k) class estimator and the r-(k,d) class estimator by conducting a simulation study and through the results and under the mean square error (MSE) criterion to find the best way to address the two problems together. The results showed that the r-(k,d) class estimator is the best esti

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Publication Date
Sun Feb 25 2024
Journal Name
Baghdad Science Journal
Hybrid Framework To Exclude Similar and Faulty Test Cases In Regression Testing
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Regression testing is a crucial phase in the software development lifecycle that makes sure that new changes/updates in the software system don’t introduce defects or don’t affect adversely the existing functionalities. However, as the software systems grow in complexity, the number of test cases in regression suite can become large which results into more testing time and resource consumption. In addition, the presence of redundant and faulty test cases may affect the efficiency of the regression testing process. Therefore, this paper presents a new Hybrid Framework to Exclude Similar & Faulty Test Cases in Regression Testing (ETCPM) that utilizes automated code analysis techniques and historical test execution data to

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Publication Date
Thu Jun 02 2011
Journal Name
Ibn Al-haithem Journal For Pure And Applied Sciences
On modified pr-test double stage shrinkage estimators for estimate the parameters of simple linear regression model
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