Grey system theory is a multidisciplinary scientific approach, which deals with systems that have partially unknown information (small sample and uncertain information). Grey modeling as an important component of such theory gives successful results with limited amount of data. Grey Models are divided into two types; univariate and multivariate grey models. The univariate grey model with one order derivative equation GM (1,1) is the base stone of the theory, it is considered the time series prediction model but it doesn’t take the relative factors in account. The traditional multivariate grey models GM(1,M) takes those factor in account but it has a complex structure and some defects in " modeling mechanism", "parameter estimation "and "model structure", So that traditional GM(1,M) submitted to many trials of optimizations to getting rid this defects. This research shows the characteristics of the traditional GM(1,M), the problems it suffer from, the method of getting rid of such problems and presents two optimized multivariable grey model of one order derivative equation. the first one is called the Optimized Grey Model abbreviated as OGM(1, M) by adding the linear correction term h1(M-1)and the grey action quantity term (h2) to the traditional model GM(1,M) the latter is called Optimized Background value Grey Model OBGM(1,M) by optimizing the Background value of the last model OGM(1,M). We use two A realistic data represents the water consumption in Baghdad at the period (2016-2022) to compare the two optimized models with the traditional represents the water consumption in Baghdad at the period (2016-2022)). we use the mean absolute percentage error (MAPE) and the determination coefficient R2. To compare the two optimized model with traditional one. The results show that the two optimized have less values than the those of the traditional model GM(I,M), and that verify the correctness of defects analysis of GM(1,M).
In 2020 one of the researchers in this paper, in his first research, tried to find out the Modified Weighted Pareto Distribution of Type I by using the Azzalini method for weighted distributions, which contain three parameters, two of them for scale while the third for shape.This research compared the distribution with two other distributions from the same family; the Standard Pareto Distribution of Type I and the Generalized Pareto Distribution by using the Maximum likelihood estimator which was derived by the researchers for Modified Weighted Pareto Distribution of Type I, then the Mont Carlo method was used–that is one of the simulation manners for generating random samples data in different sizes ( n= 10,30,50), and in di
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تناولنا في بحثنا أحد اساليب البرمجة الخطية وهي الطريقة المبسطة لتقدير معلمات انموذج الانحدار الخطي عن طريق اختيار دالة الهدف التي تعمل على تقليل الحد الادنى لمجموع الاخطاء الناتجة من تقدير المعلمات بطريقة المربعات الصغرى الاعتيادية ( OLS) حيث سيتم في الطريقة المبسطة ( simplex) فرض قيود على نفس الاخطاء نفسها بهدف تصغيرها الى اقل ما يمكن للحصول على تقديرات افضل لمعلمات انموذج الانحدار الخطي . على اساس ان طريقة المرب
... Show MoreIn this paper, an algorithm for binary codebook design has been used in vector quantization technique, which is used to improve the acceptability of the absolute moment block truncation coding (AMBTC) method. Vector quantization (VQ) method is used to compress the bitmap (the output proposed from the first method (AMBTC)). In this paper, the binary codebook can be engender for many images depending on randomly chosen to the code vectors from a set of binary images vectors, and this codebook is then used to compress all bitmaps of these images. The chosen of the bitmap of image in order to compress it by using this codebook based on the criterion of the average bitmap replacement error (ABPRE). This paper is suitable to reduce bit rates
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Water quality planning relies on Biochemical Oxygen Demand BOD. BOD testing takes five days. The Particle Swarm Optimization (PSO) is increasingly used for water resource forecasting. This work designed a PSO technique for estimating everyday BOD at Al-Rustumiya wastewater treatment facility inlet. Al-Rustumiya wastewater treatment plant provided 702 plant-scale data sets during 2012-2022. The PSO model uses the daily data of the water quality parameters, including chemical oxygen demand (COD), chloride (Cl-), suspended solid (SS), total dissolved solids (TDS), and pH, to determine how each variable affects the daily incoming BOD. PSO and multiple linear regression (MLR) findings are compared, and their perfor
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Health service institutions suffer from challenges resulting from the great changes that our world is witnessing today. This has affected the value that these institutions add to the patient.
This research aims to identify the effect of integrating each of the techniques of QFD and value engineering for the health services provided to the patient to improve the value for him and thus obtain his satisfaction, which is reflected in the reputation of the surveyed hospitals. To achieve this, the descriptive analytical method was used, and a questionnaire was designed to collect the necessary data, which represents a measure of this research. The questionnaire was distri
... Show MoreIn this research was the study of a single method of estimation and testing parameters mediating variables (Mediation) in a specimen structural equations SEM a bootstrap method, for the purpose of application of the integrated survey of the situation Marital data and health mirror Iraqi (I-WISH) for the year 2011 from the Ministry of Planning - device Central Bureau of Statistics, and applied to the appropriate data from the terms of the data to a form of structural equation SEM using factor analysis affirmative (Confirmatory Factor analysis) CFA As a way to see the match variables that make up the model, and after confirming the model matching or suitability are having the effect of variables mediation in the model tested by the
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Generalized multivariate transmuted Bessel distribution belongs to the family of probability distributions with a symmetric heavy tail. It is considered a mixed continuous probability distribution. It is the result of mixing the multivariate Gaussian mixture distribution with the generalized inverse normal distribution. On this basis, the paper will study a multiple compact regression model when the random error follows a generalized multivariate transmuted Bessel distribution. Assuming that the shape parameters are known, the parameters of the multiple compact regression model will be estimated using the maximum likelihood method and Bayesian approach depending on non-informative prior information. In addition, the Bayes factor was used
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This paper study two stratified quantile regression models of the marginal and the conditional varieties. We estimate the quantile functions of these models by using two nonparametric methods of smoothing spline (B-spline) and kernel regression (Nadaraya-Watson). The estimates can be obtained by solve nonparametric quantile regression problem which means minimizing the quantile regression objective functions and using the approach of varying coefficient models. The main goal is discussing the comparison between the estimators of the two nonparametric methods and adopting the best one between them
Purpose: The research aims to estimate models representing phenomena that follow the logic of circular (angular) data, accounting for the 24-hour periodicity in measurement. Theoretical framework: The regression model is developed to account for the periodic nature of the circular scale, considering the periodicity in the dependent variable y, the explanatory variables x, or both. Design/methodology/approach: Two estimation methods were applied: a parametric model, represented by the Simple Circular Regression (SCR) model, and a nonparametric model, represented by the Nadaraya-Watson Circular Regression (NW) model. The analysis used real data from 50 patients at Al-Kindi Teaching Hospital in Baghdad. Findings: The Mean Circular Erro
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