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).
The study aimed to investigate the relationship between the multiple intelligence and the numerical sense. The chosen population of the study was the 4th secondary stage students. The sample consisted of 400 female and male student. The researcher utilized two test; multiple intelligence test which include three categories of intelligence (logical-mathematical, spatial, and linguistics) consisted of (36) item, and the numerical sense test that consisted of (44) item. The two tests were constructed by the researcher himself. The psychometric properties of the test were also verified. The results showed that there was a correlation between the multiple intelligence and the numerical sense as well as the students’ means scores
... Show MoreThe aim of the research is to examine the multiple intelligence test item selection based on Howard Gardner's MI model using the Generalized Partial Estimation Form, generalized intelligence. The researcher adopted the scale of multiple intelligences by Kardner, it consists of (102) items with eight sub-scales. The sample consisted of (550) students from Baghdad universities, Technology University, al-Mustansiriyah university, and Iraqi University for the academic year (2019/2020). It was verified assumptions theory response to a single (one-dimensional, local autonomy, the curve of individual characteristics, speed factor and application), and analysis of the data according to specimen partial appreciation of the generalized, and limits
... Show Moreدُرِست العوامل المؤثرة في عدد ساعات تجهيز الكهرباء في مدينة بغداد، وتكونت عينة الدراسة من (365) مشاهدة يومية لعام 2018، وتمثلت بستة متغيرات استعملت في الدراسة. كان الهدف الرئيس هو دراسة العلاقة بين هذه المتغيرات، وتقدير تأثيرات المتغيرات التنبؤية في المتغير التابع (عدد ساعات تجهيز الكهرباء في مدينة بغداد). ولتحقيق ذلك استعملت نمذجة المعادلات الهيكلية/ تحليل المسار وبرنامج AMOS
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The multiple linear regression model is an important regression model that has attracted many researchers in different fields including applied mathematics, business, medicine, and social sciences , Linear regression models involving a large number of independent variables are poorly performing due to large variation and lead to inaccurate conclusions , One of the most important problems in the regression analysis is the multicollinearity Problem, which is considered one of the most important problems that has become known to many researchers , As well as their effects on the multiple linear regression model, In addition to multicollinearity, the problem of outliers in data is one of the difficulties in constructing the reg
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The present study aimed to estimate percentage of red and white muscles fibers in two species of bony fishes belong to two different families which represented by Tenualosa ilisha (Hamilton , 1822) that belongs to the family Clupeidae and Cyprinus carpio (Linnaeus , 1758) that belongs to the family Cyprinidae . The samples were collected from local market at holy Karbala province. The results show difference clear in mean values of muscles numbers at different studied length groups, and the percentage of red muscles fibers were less than that of white muscle fibers at different body regions (R1,R2,and R3) among species. The total average of red muscle fibers values ranged between (4.23 - 11.08 %) while the total average of wh
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This study is studied one method of estimation and testing parameters mediating variables in a structural equations model SEM is causal steps method, in order to identify and know the variables that have indirect effects by estimating and testing mediation variables parameters by the above way and then applied to Iraq Women Integrated Social and Health Survey (I-WISH) for year 2011 from the Ministry of planning - Central statistical organization to identify if the variables having the effect of mediation in the model by the step causal methods by using AMOS program V.23, it was the independent variable X represents a phenomenon studied (cultural case of the
The aim of this paper is to present a method for solving of system of first order initial value problems of ordinary differential equation by a semi-analytic technique with constructing polynomial solutions for decreasing dangers of lead. The original problem is concerned using two-point osculatory interpolation with the fit equals numbers of derivatives at the end points of an interval [0 , 1].
This paper is attempt to study the nonlinear second order delay multi-value problems. We want to say that the properties of such kind of problems are the same as the properties of those with out delay just more technically involved. Our results discuss several known properties, introduce some notations and definitions. We also give an approximate solution to the coined problems using the Galerkin's method.
The aim of this paper is to present a semi - analytic technique for solving singular initial value problems of ordinary differential equations with a singularity of different kinds to construct polynomial solution using two point osculatory interpolation. The efficiency and accuracy of suggested method is assessed by comparisons with exact and other approximate solutions for a wide classes of non–homogeneous, non–linear singular initial value problems. A new, efficient estimate of the global error is used for adaptive mesh selection. Also, analyze some of the numerical aspects
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