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Intelligence framework dust forecasting using regression algorithms models
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<span>Dust is a common cause of health risks and also a cause of climate change, one of the most threatening problems to humans. In the recent decade, climate change in Iraq, typified by increased droughts and deserts, has generated numerous environmental issues. This study forecasts dust in five central Iraqi districts using machine learning and five regression algorithm supervised learning system framework. It was assessed using an Iraqi meteorological organization and seismology (IMOS) dataset. Simulation results show that the gradient boosting regressor (GBR) has a mean square error of 8.345 and a total accuracy ratio of 91.65%. Moreover, the results show that the decision tree (DT), where the mean square error is 8.965, comes in second place with a gross ratio of 91%. Furthermore, Bayesian ridge (BR), linear regressor (LR), and stochastic gradient descent (SGD), with mean square error and with accuracy ratios of 84.365%, 84.363%, and 79%. As a result, the performance precision of these regression models yields. The interaction framework was designed to be a straightforward tool for working with this paradigm. This model is a valuable tool for establishing strategies to counter the swiftness of climate change in the area under study.</span>

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Publication Date
Wed Sep 30 2026
Journal Name
International Journal Of Intelligent Engineering And Systems
Performance Evaluation of Fragmentation Metrics in Elastic Optical Networks: A Comprehensive Analysis and Classification Framework
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Publication Date
Thu Jun 01 2017
Journal Name
Journal Of Economics And Administrative Sciences
The Role of Strategic audit in detection of financial corruption cases in Iraq - Proposed Framework
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This research focuses on detecting the financial corruption cases in Iraq in light of adoption the strategic audit, the paper deals with the problem of the proliferation corruption cases particularly financial in Iraq and dramatically in the presence of audit and control devices as well as inspection and integrity devices, which indicates the existence of deficiencies and weaknesses in those devices in the implementation of audit and control functions in order to detect the corruption cases in the economic units in Iraq.

Stems objective of this research through the provision of approach of strategic audit concepts and indicate the extent importance of adopting of strategic audit as a means to detect the f

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Publication Date
Thu Nov 16 2017
Journal Name
Joiv : International Journal On Informatics Visualization
Multilayered Framework to Enhance Management Information Systems Decision on Sensitive Data in Cloud Computing Environment
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The purpose of this research is defining the main factors influencing on decision of management system on sensitive data in cloud. The framework is proposed to enhance management information systems decision on sensitive information in cloud environment. The structured interview with several security experts working on cloud computing security to investigate the main objective of framework and suitability of instrument, a pilot study conducts to test the instrument. The validity and reliability test results expose that study can be expanded and lead to final framework validation. This framework using multilevel related to Authorization, Authentication, Classification and identity anonymity, and save and verify, to enhance management

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Publication Date
Sun Feb 03 2019
Journal Name
Journal Of Accounting And Financial Studies ( Jafs )
Use Dividend Discount Model , DDM in Stocks Valuation With Framework of Inflation: An Applied Study
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The theme of this Study presents analysis and discuss to the "Share the framework for assessing inflation," a practical study in a sample of joint stock companies listed on the Iraq Stock Exchange for the years (2009-2013). To determine the extent of the disparity between the nominal value of shares (Nominal Value) before deducting inflation and the real value (Real Value) per share, after deducting inflation in the case of zero growth. The study relied on annual reports of the companies of the research sample of the Iraq Stock Exchange, as well as the Iraqi Securities Commission. Besides the annual reports issued by the Ministry of Planning, as well as annual reports and statistical bulletin issued by the Central Bank of Iraq. It is fra

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Publication Date
Tue Oct 23 2018
Journal Name
Journal Of Economics And Administrative Sciences
Compare some wavelet estimators for parameters in the linear regression model with errors follows ARFIMA model.
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The aim of this research is to estimate the parameters of the linear regression model with errors following ARFIMA model by using wavelet method depending on maximum likelihood and approaching general least square as well as ordinary least square. We use the estimators in practical application on real data, which were the monthly data of Inflation and Dollar exchange rate obtained from the (CSO) Central Statistical organization for the period from 1/2005 to 12/2015. The results proved that (WML) was the most reliable and efficient from the other estimators, also the results provide that the changing of fractional difference parameter (d) doesn’t effect on the results.

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Publication Date
Mon Apr 13 2026
Journal Name
Innovative Infrastructure Solutions
Beyond empiricism: a unified physics-based framework for resonance avoidance and carbon-efficient mass optimization of machine foundations
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Dynamic machine foundations can be considered as a necessary component of the industrial infrastructure. Design of the dynamic equipment foundations has, however, traditionally been grounded on a rule of thumb that is inaccurate and rigid to use at the discretion of the engineers. The conventional rule of thumb, which includes minimum weight ratios and resonance avoidance criteria, has been used singularly with two poles, which can be either conservatively designed systems that are too heavy, or systems that are going to experience too much vibration and fatigue. This paper presents a novel, analytical framework for the reinterpretation of traditional design practices, using a physics-based approach, and results in a single, unified overall

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Publication Date
Thu Dec 12 2013
Journal Name
Iraqi Journal Of Science
Determination of Optimum Mechanical Drilling Parameters for an Iraqi Field with Regression Model
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Publication Date
Mon May 26 2025
Journal Name
Journal Of Al-rafidain University College For Sciences ( Print Issn: 1681-6870 ,online Issn: 2790-2293 )
The Use of Cone Projections and Quadratic programming in Estimation of Constrained Regression
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Statisticians often use regression models like parametric, nonparametric, and semi-parametric models to represent economic and social phenomena. These models explain the relationships between different variables in these phenomena. One of the parametric model techniques is conic projection regression. It helps to find the most important slopes for multidimensional data using prior information about the regression's parameters to estimate the most efficient estimator. R algorithms, written in the R language, simplify this complex method. These algorithms are based on quadratic programming, which makes the estimations more accurate.

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Publication Date
Tue Apr 04 2023
Journal Name
Journal Of Techniques
Comparison Between the Kernel Functions Used in Estimating the Fuzzy Regression Discontinuous Model
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Some experiments need to know the extent of their usefulness to continue providing them or not. This is done through the fuzzy regression discontinuous model, where the Epanechnikov Kernel and Triangular Kernel were used to estimate the model by generating data from the Monte Carlo experiment and comparing the results obtained. It was found that the. Epanechnikov Kernel has a least mean squared error.

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Publication Date
Sun Oct 01 2017
Journal Name
Journal Of Economics And Administrative Sciences
discriminate analysis and logistic regression existence of multicolleniarty problem(Empirical Study on Anemia)
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The method binery logistic regression and linear discrimint function of the most important statistical methods used in the classification and prediction when the data of the kind of binery (0,1) you can not use the normal regression therefore resort to binary logistic regression and linear discriminant function in the case of two group in the case of a Multicollinearity problem between the data (the data containing high correlation) It became not possible to use binary logistic regression and linear discriminant function, to solve this problem, we resort to Partial least square regression.

In this, search the comparison between binary lo

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