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A Comparison Between Membership Function And Entropy Function In Fuzzy Adaptive Linear Regression
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Abstract        There are many uncertainty sources that may affect the statistical reasoning. However, traditional methods can not deal with all kinds of uncertainty sources, which has led many researchers to develop traditional methods. Studies still exist to this day, making hypotheses to create a common understanding for the purpose of reaching new solutions through the use of new methods that combine traditional and modern theories of sources of uncertainty        The aim of current study was to develop the adaptive fuzzy linear regression model in the case of using inaccurate data as the source of uncertainty. Specifically, the model proposed by [1]. However, instead of what dominant in fuzzy linear regression analysis, we used a new born method that uses the positions and entropy to fuzzification instead membership function. As for the comparison method we used the mean absolute difference as performance's accuracy measures.         The results of this study showed the efficiency of the use of the position and the entropy function to describe the fuzzy numbers over the use of the membership functions. The results also indicated that the develop model has the best results compared to the model adapted using the membershop functions in [1].

Publication Date
Mon Aug 01 2022
Journal Name
Baghdad Science Journal
Lymphocytes Prediction of Homeostasis Model Assessment of Beta-cells Function (HOMA-B) and C-peptide Level during Pregnancy: New Insight into Beta-cells Proliferation and Insulin Sensitivity
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This work aims to detect the associations of C-peptide and the homeostasis model assessment of beta-cells function (HOMA2-B%) with inflammatory biomarkers in pregnant-women in comparison with non-pregnant women. Sera of 28 normal pregnant women at late pregnancy versus 27 matched age non-pregnant women (control), were used to estimate C-peptide, triiodothyronine (T3), and thyroxin (T4) by Enzyme-linked-immunosorbent assay (ELISA), fasting blood sugar (FBS) by automatic analyzer Biolis 24i, hematology-tests by hematology analyzer and the calculation of HOMA2-B% and homeostasis model assessment of insulin sensitivity (HOMA2-S%) by using C-peptide values instead of insulin. The comparisons, correlations, regression analysis tests were perfo

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Publication Date
Mon Sep 30 2024
Journal Name
Joiv : International Journal On Informatics Visualization
Evaluation of the Performance of Kernel Non-parametric Regression and Ordinary Least Squares Regression
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Researchers need to understand the differences between parametric and nonparametric regression models and how they work with available information about the relationship between response and explanatory variables and the distribution of random errors. This paper proposes a new nonparametric regression function for the kernel and employs it with the Nadaraya-Watson kernel estimator method and the Gaussian kernel function. The proposed kernel function (AMS) is then compared to the Gaussian kernel and the traditional parametric method, the ordinary least squares method (OLS). The objective of this study is to examine the effectiveness of nonparametric regression and identify the best-performing model when employing the Nadaraya-Watson

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Publication Date
Fri Nov 03 2023
Journal Name
Lecture Notes In Electrical Engineering
A Survey Study and Comparison of Drones Communication Systems
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Publication Date
Wed Mar 10 2021
Journal Name
Baghdad Science Journal
Fuzzy Subspaces For Fuzzy space of Orderings
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The purpose of this paper is to define fuzzy subspaces for fuzzy space of orderings and we prove some results about this definition in which it leads to a lot of new results on fuzzy space of orderings. Also we define the sum and product over such spaces such that: If f = < a1,…,an > and g = < b1,…bm>, their sum and product are f + g = < a1…,an, b1, …, bm> and f × g =. for all a1,…,an,b1,…,bm ? G

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Publication Date
Tue Jun 01 2021
Journal Name
International Journal Of Nonlinear Analysis And Applications
Bayes estimators of a multivariate generalized hyperbolic partial regression model
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Publication Date
Mon Apr 20 2020
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
Interval Value Fuzzy k-Ideals of a KU-Semigroup
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The notion of interval value fuzzy k-ideal of KU-semigroup was studied as a generalization of afuzzy k-ideal of KU-semigroup. Some results of this idea under homomorphism are discussed. Also, we presented some properties about the image (pre-image) for interval~ valued fuzzy~k-ideals of a KU-semigroup. Finally, the~ product of~ interval valued fuzzyk-ideals is established.

Publication Date
Tue Dec 20 2022
Journal Name
Biomedical And Pharmacology Journal
Phytochemical Comparison Study for Evaluating the Hypolipidemic Effect Between Two Iraqi Pepper Spp in the Rats Model.
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Hypercholesterolemia is a predominant risk factor for atherosclerosis and cardiovascular disease (CVD). The World Health Organization (WHO), ) recommended reducing the intake of cholesterol and saturated fats. On the other hand, limited evidence is available on the benefits of vegetables in the diet to reduce these risk factors, so this research was conducted to compare the hypolipidemic effect between the extracts of two different types of Iraqi peppers, the fruit of the genus Capsicum traditionally known as red pepper extract (RPE), and Piper nigrum as black pepper extract (BPE), respectively, in different parameters and histology of the liver of the experimental animals. The red pepper was extracted by ethyl acetate, while the black pepp

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Publication Date
Sat Jun 01 2019
Journal Name
Journal Of Economics And Administrative Sciences
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 numbe

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Publication Date
Tue Mar 01 2011
Journal Name
Journal Of Economics And Administrative Sciences
Laplace Distribution And Probabilistic (bi) In Linear Programming Model
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The theory of probabilistic programming  may be conceived in several different ways. As a method of programming it analyses the implications of probabilistic variations in the parameter space of linear or nonlinear programming model. The generating mechanism of such probabilistic variations in the economic models may be due to incomplete information about changes in demand, pro­duction and technology, specification errors about the econometric relations presumed for different economic agents, uncertainty of various sorts and the consequences of imperfect aggregation or disaggregating of economic variables. In this Research we discuss the probabilistic programming problem when the coefficient bi is random variable

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Publication Date
Thu Dec 01 2022
Journal Name
Neuroscience Informatics
Epileptic EEG activity detection for children using entropy-based biomarkers
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