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مقارنة الانحدار الشرائحي المعكوس مع المركبات الرئيسة في اختزال البيانات ذات الابعاد العالية بأستعمال المحاكاة
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 يدرس هذا البحث طرائق اختزال الابعاد التي تعمل على تجاوز مشكلة البعدية عندما تفشل الطرائق التقليدية في ايجاد تقدير جيد للمعلمات، لذلك يتوجب التعامل مع هذه المشكلة بشكل مباشر. ومن اجل ذلك، يجب التخلص من هذه المشكلة لذا تم استعمال اسلوبين لحل مشكلة البيانات ذات الابعاد العالية الاسلوب الاول طريقة الانحدار الشرائحي المعكوس SIR ) ) والتي تعتبر طريقة غير كلاسيكية  وكذلك طريقة ( WSIR ) المقترحة والاسلوب الثاني طريقة المركبات الرئيسة ( PCA ) وهي الطريقة العامة المستخدمة في اختزال الابعاد ,  ان عمل طريقة انحدار الشرائحي المعكوس SIR ) ) و طريقة المركبات الرئيسة (PCA) يقوم على عمل توليفات خطية مختزلة من مجموعة جزئية من المتغيرات التوضيحية الأصلية والتي قد تعاني من مشكلة عدم التجانس ومن مشكلة التعدد الخطي بين معظم المتغيرات التوضيحية , وستقوم هذه التوليفات الجديدة المتمثلة بالمركبات الخطية الناتجة من الطريقتين بإختزال أكثر عدد من المتغيرات التوضيحية للوصول الى بُعد جديد واحد او اكثر  يسمى بالبعد الفعّال . وسيتم استعمال معيار جذر متوسط مربعات الخطأ للمقارنة بين الاسلوبين لبيان  افضلية الطرائق , وقد تم اجراء دراسة محاكاة للمقارنة بين الطرائق المستعملة  وقد بينت نتائج المحاكاة ان طريقة weight standard Sir  المقترحة هي الافضل .

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Publication Date
Fri Dec 12 2025
Journal Name
Journal Of Administration And Economics
Bayesian Method in Classification Regression Tree to estimate nonparametric additive model compared with Logistic Model with Application
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The use of Bayesian approach has the promise of features indicative of regression analysis model classification tree to take advantage of the above information by, and ensemble trees for explanatory variables are all together and at every stage on the other. In addition to obtaining the subsequent information at each node in the construction of these classification tree. Although bayesian estimates is generally accurate, but it seems that the logistic model is still a good competitor in the field of binary responses through its flexibility and mathematical representation. So is the use of three research methods data processing is carried out, namely: logistic model, and model classification regression tree, and bayesian regression tree mode

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Publication Date
Sat Oct 01 2022
Journal Name
Journal Of Engineering
Evaluation of ANFIS and Regression Techniques in Estimating Soil Compression Index for Cohesive soils
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Generally, direct measurement of soil compression index (Cc) is expensive and time-consuming. To save time and effort, indirect methods to obtain Cc may be an inexpensive option. Usually, the indirect methods are based on a correlation between some easier measuring descriptive variables such as liquid limit, soil density, and natural water content. This study used the ANFIS and regression methods to obtain Cc indirectly. To achieve the aim of this investigation, 177 undisturbed samples were collected from the cohesive soil in Sulaymaniyah Governorate in Iraq. Results of this study indicated that ANFIS models over-performed the Regression method in estimating Cc with R2 of 0.66 and 0.48 for both ANFIS and Regre

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Publication Date
Sat Jan 13 2018
Journal Name
Journal Of Engineering
Regression Analysis Models to Predict the 28 -day Compressive Strength Using Accelerated Curing Tests
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Regression analysis models are adopted by using SPSS program to predict the 28-day compressive strength as dependent variable and the accelerated compressive strength as independent variable. Three accelerated curing method was adopted, warm water (35ºC) and autogenous according to ASTM C C684-99 and the British method (55ºC) according to BS1881: Part 112:1983. The experimental concrete mix design was according to ACI 211.1. Twenty eight concrete mixes with slump rang (25-50) mm and (75-100)mm for rounded and crushed coarse aggregate with cement content (585, 512, 455, 410, 372 and 341)Kg/m3.

      The experimental results showed that the acc

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Publication Date
Sat Dec 02 2017
Journal Name
Al-khwarizmi Engineering Journal
Direction Finding Using GHA Neural Networks
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 This paper adapted the neural network for the estimating of the direction of arrival (DOA). It uses an unsupervised adaptive neural network with GHA algorithm to extract the principal components that in turn, are used by Capon method to estimate the DOA, where by the PCA neural network we take signal subspace only and use it in Capon (i.e. we will ignore the noise subspace, and take the signal subspace only).

 

 

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Publication Date
Mon Mar 31 2025
Journal Name
International Journal Of Advanced Technology And Engineering Exploration
Breast cancer survival rate prediction using multimodal deep learning with multigenetic features
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Breast cancer is a heterogeneous disease characterized by molecular complexity. This research utilized three genetic expression profiles—gene expression, deoxyribonucleic acid (DNA) methylation, and micro ribonucleic acid (miRNA) expression—to deepen the understanding of breast cancer biology and contribute to the development of a reliable survival rate prediction model. During the preprocessing phase, principal component analysis (PCA) was applied to reduce the dimensionality of each dataset before computing consensus features across the three omics datasets. By integrating these datasets with the consensus features, the model's ability to uncover deep connections within the data was significantly improved. The proposed multimodal deep

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Publication Date
Sat Dec 31 2022
Journal Name
Journal Of Economics And Administrative Sciences
Estimation of Causal Effect of treatment via Fuzzy Regression Discontinuity Designs
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In some cases, researchers need to know the causal effect of the treatment in order to know the extent of the effect of the treatment on the sample in order to continue to give the treatment or stop the treatment because it is of no use. The local weighted least squares method was used to estimate the parameters of the fuzzy regression discontinuous model, and the local polynomial method was used to estimate the bandwidth. Data were generated with sample sizes (75,100,125,150 ) in repetition 1000. An experiment was conducted at the Innovation Institute for remedial lessons in 2021 for 72 students participating in the institute and data collection. Those who used the treatment had an increase in their score after

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Publication Date
Mon Jan 09 2017
Journal Name
Nauchform
Creolized Text as a Means of Modern Communication: Verbal and Visual Components
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The article considers a creolized text as a means of modern communication, describing its key verbal and visual components; the relationship of concepts polycode and creolized text has been shown; the universal basic image features have been called; the following kinds of creolized texts have been distinguished; it has been proved that the effective means of attracting the attention of the addressee is the use of expressive font features, which are divided into two groups: topographics (mechanisms of varying of areal syntagmatic of a text) and supragraphcs (change of typeface of font).

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Publication Date
Fri Oct 01 2021
Journal Name
Journal Of Al-rafidain University College For Sciences ( Print Issn: 1681-6870 ,online Issn: 2790-2293 )
The Use of Logistic Regression Model in Estimating the Probability of Being Affected By Breast Cancer Based On the Levels of Interleukins and Cancer Marker CA15-3
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Breast cancer has got much attention in the recent years as it is a one of the complex diseases that can threaten people lives. It can be determined from the levels of secreted proteins in the blood. In this project, we developed a method of finding a threshold to classify the probability of being affected by it in a population based on the levels of the related proteins in relatively small case-control samples. We applied our method to simulated and real data. The results showed that the method we used was accurate in estimating the probability of being diseased in both simulation and real data. Moreover, we were able to calculate the sensitivity and specificity under the null hypothesis of our research question of being diseased o

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Publication Date
Sun Apr 06 2014
Journal Name
Journal Of Economics And Administrative Sciences
Modeling Absolute Deviations Method by using Numerical Methods to measure the dispersion of the proposal for error
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Is in this research review of the way minimum absolute deviations values ​​based on linear programming method to estimate the parameters of simple linear regression model and give an overview of this model. We were modeling method deviations of the absolute values ​​proposed using a scale of dispersion and composition of a simple linear regression model based on the proposed measure. Object of the work is to find the capabilities of not affected by abnormal values by using numerical method and at the lowest possible recurrence.

 

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Publication Date
Thu Sep 30 2021
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Development a Statistical Relationship between Compressional Wave Velocity and Petrophysical Properties from Logs Data for JERIBE Formation ASMARI Reservoir in FAUQI Oil Field
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   The Compressional-wave (Vp) data are useful for reservoir exploration, drilling operations, stimulation, hydraulic fracturing employment, and development plans for a specific reservoir. Due to the different nature and behavior of the influencing parameters, more complex nonlinearity exists for Vp modeling purposes. In this study, a statistical relationship between compressional wave velocity and petrophysical parameters was developed from wireline log data for Jeribe formation in Fauqi oil field south Est Iraq, which is studied using single and multiple linear regressions. The model concentrated on predicting compressional wave velocity from petrophysical parameters and any pair of shear waves velocity, porosity, density, a

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