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).
Abstract:
We can notice cluster data in social, health and behavioral sciences, so this type of data have a link between its observations and we can express these clusters through the relationship between measurements on units within the same group.
In this research, I estimate the reliability function of cluster function by using the seemingly unrelate
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In this research work, a simulator with time-domain visualizers and configurable parameters using a continuous time simulation approach with Matlab R2019a is presented for modeling and investigating the performance of optical fiber and free-space quantum channels as a part of a generic quantum key distribution system simulator. The modeled optical fiber quantum channel is characterized with a maximum allowable distance of 150 km with 0.2 dB/km at =1550nm. While, at =900nm and =830nm the attenuation values are 2 dB/km and 3 dB/km respectively. The modeled free space quantum channel is characterized at 0.1 dB/km at =860 nm with maximum allowable distance of 150 km also. The simulator was investigated in terms of the execution of the BB84 prot
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The aim of this paper is to derive a posteriori error estimates for semilinear parabolic interface problems. More specifically, optimal order a posteriori error analysis in the - norm for semidiscrete semilinear parabolic interface problems is derived by using elliptic reconstruction technique introduced by Makridakis and Nochetto in (2003). A key idea for this technique is the use of error estimators derived for elliptic interface problems to obtain parabolic estimators that are of optimal order in space and time.
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The ground state properties including the density distributions of the neutrons, protons and matter as well as the corresponding root mean square (rms) radii of proton-rich halo candidates 8B, 12N, 23Al and 27P have been studied by the single particle Bear– Hodgson (BH) wave functions with the two-body model of (core+p). It is found that the rms radii of these proton-rich nuclei are reproduced well by this model and the radial wave functions describe the long tail of the proton and matter density distributions. These results indicate that this model achieves a suitable description of the possible halo structure. The plane wave Born approximation (PWBA) has been used to compute the elastic charge form factors.
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Multiple sclerosis (MS) is a neurodegenerative disorder with various clinical types. Glial fibrillary acidic protein (GFAP) is significantly elevated in the cerebrospinal fluid (CSF) of MS patients compared with that of healthy controls. The aim of this study is to evaluate serum levels of GFAP in relation to disease activity in relapsing-remitting MS patients and to compare them with those of healthy controls. Method: This study involved 58 MS patients of relapsing-remitting MS (RRMS) type, 22 in an active stage of the disease and 36 in remission, and 50 healthy individuals as age- and sex-matched controls. Blood samples were taken from the patients at the MS Clinic of the Baghdad Teaching Hospital, and the serum levels of GFAP were determ
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يعد تحليل السلاسل الزمنية من المواضـيع الهامة في تفسير الظـواهر التي تحدث خلال فترة زمنية معينة. ان الهدف من هذا لتحليل هو الحصـول على وصف وبنـاء أنموذج مناسب من اجل اعطاء صورة مستقبلية واضحة للسلاسل الزمنية المدروسة وان السلاسل الزمنية اهم الادوات المستخدمة في بناء وتقدير والتنبؤ بالظواهر المختلفة وان الاستدامة المالية هي الحالة التي تكون فيها الدولة قادرة على الوفاء بالتزاماتها الحالية والمستقبلية من غي
... Show MoreIn this paper the method of singular value decomposition is used to estimate the ridge parameter of ridge regression estimator which is an alternative to ordinary least squares estimator when the general linear regression model suffer from near multicollinearity.
This paper deals the prediction of the process of random spatial data of two properties, the first is called Primary variables and the second is called secondary variables , the method that were used in the prediction process for this type of data is technique Co-kriging , the method is usually used when the number of primary variables meant to predict for one of its elements is measured in a particular location a few (because of the cost or difficulty of obtaining them) compare with secondary variable which is the number of elements are available and highly correlated with primary variables, as was the&nbs
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MCA has gained a reputation for being a very useful statistical method for determining the association between two or more categorical variables and their graphical description. For performance this method, we must calculate the singular vectors through (SVD). Which is an important primary tool that allows user to construct a low-dimensional space to describe the association between the variables categories. As an alternative procedure to use (SVD), we can use the (BMD) method, which involves using orthogonal polynomials to reflect the structure of ordered categorical responses. When the features of BMD are combined with SVD, the (HD) is formed. The aim of study is to use alternative method of (MCA) that is appropriate with order
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