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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
Sun Feb 28 2021
Journal Name
Journal Of Economics And Administrative Sciences
Enhancing national security through foreseeing the economic intelligence system in Iraq
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         Economic intelligence represents a modern field of knowledge that has been and is still the focus of many studies and research, including this research that deals with economic intelligence and its role in strengthening Iraqi national security - an analytical study. Economic development and economic development without security, and in a situation such as that of Iraq, which is still suffering from conflicts, conflicts and the effects of wars, as well as the unstable conditions in its regional environment, the directions of that relationship cannot be determined except through the availability of accurate information, indicators, full knowledge of reality and the pos

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Publication Date
Fri Mar 01 2024
Journal Name
International Journal Of Medical Informatics
An artificial intelligence approach to predict infants’ health status at birth
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Publication Date
Thu Jun 01 2017
Journal Name
Journal Of Economics And Administrative Sciences
The Role Of Cultural Intelligence In drawing Local Politics (Field Research)
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Abstract :

This research aims to examine the correlation and the impact of Cultural Intelligence with their dimensions (Strategy, Knowledge, Motivation, Behavior) on Drawing Local politics and their dimensions (Empowerment, Flexibility, Organizational Justice, Local Funding) In Dhi Qar Provincial Council To determine the extent of the presence of significant statistical differences between research variables Due to the recent experiment which requires clarification of the role of the pivotal and important carried out by the provincial council in the exercise of his work in light of the diversity of cultures and the peculiarities of the local community, which may impede the provision of equal services to all those parties

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Publication Date
Fri Jan 01 2021
Journal Name
Artificial Intelligence For Covid-19
An Efficient Mixture of Deep and Machine Learning Models for COVID-19 and Tuberculosis Detection Using X-Ray Images in Resource Limited Settings
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Publication Date
Tue Jun 30 2020
Journal Name
Journal Of Economics And Administrative Sciences
Using ARIMA models to forecast the volume of cargo handled in Iraqi ports An applied study in the general company of Iraqi ports
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Time series is an important statistical method adopted in the analysis of phenomena, practices, and events in all areas during specific time periods and predict future values ​​contribute to give a rough estimate of the status of the study, so the study aimed to adopt the ARIMA models to forecast the volume of cargo handled and achieved in four ports (Umm Qasr Port, Khor Al Zubair Port, Abu Flus Port, and Maqal Port(, Monthly data on the volume of cargo handled for the years (2006-2018) were collected (156) observations. The study found that the most efficient model is ARIMA (1,1,1).

The volume of go

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Publication Date
Mon Feb 04 2019
Journal Name
Journal Of Accounting And Financial Studies ( Jafs )
Using Regression Analysis as Analytical Procedure to Facilitate the Decision-Making Process in The Tax Audit: An Applied Research in the General Commission of Taxes
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This research aims to clarify the advantages of using the regression method as analytical procedure in the tax audit to reducing the examination cost , time, effort, human and material resources, and represents an applied study in the General Commission of taxes. In order to achieve its objectives the research has used in the theoretical side the descriptive approach (analytical), and in the practical side regression method has been applied to the research sample represented by the soft drinks company that is subject to the tax settlement for the year 2014, where the value of sales has been verified by using the regression method without conductinga comprehensive examination. The most important results of the research indicate that the r

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Publication Date
Sat Aug 09 2025
Journal Name
Scientific Reports
Machine learning models for predicting morphological traits and optimizing genotype and planting date in roselle (Hibiscus Sabdariffa L.)
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Accurate prediction and optimization of morphological traits in Roselle are essential for enhancing crop productivity and adaptability to diverse environments. In the present study, a machine learning framework was developed using Random Forest and Multi-layer Perceptron algorithms to model and predict key morphological traits, branch number, growth period, boll number, and seed number per plant, based on genotype and planting date. The dataset was generated from a field experiment involving ten Roselle genotypes and five planting dates. Both RF and MLP exhibited robust predictive capabilities; however, RF (R² = 0.84) demonstrated superior performance compared to MLP (R² = 0.80), underscoring its efficacy in capturing the nonlinear genoty

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Publication Date
Mon Jul 05 2010
Journal Name
Evolutionary Algorithms
Variants of Hybrid Genetic Algorithms for Optimizing Likelihood ARMA Model Function and Many of Problems
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Optimization is essentially the art, science and mathematics of choosing the best among a given set of finite or infinite alternatives. Though currently optimization is an interdisciplinary subject cutting through the boundaries of mathematics, economics, engineering, natural sciences, and many other fields of human Endeavour it had its root in antiquity. In modern day language the problem mathematically is as follows - Among all closed curves of a given length find the one that closes maximum area. This is called the Isoperimetric problem. This problem is now mentioned in a regular fashion in any course in the Calculus of Variations. However, most problems of antiquity came from geometry and since there were no general methods to solve suc

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Publication Date
Tue Apr 26 2011
Journal Name
Evolutionary Algorithms
Variants of Hybrid Genetic Algorithms for Optimizing Likelihood ARMA Model Function and Many of Problems
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Publication Date
Fri Jan 01 2016
Journal Name
Journal Of Engineering
Improve the Performance of PID Controller by Two Algorithms for Controlling the DC Servo Motor
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The paper uses the Direct Synthesis (DS) method for tuning the Proportional Integral Derivative (PID) controller for controlling the DC servo motor. Two algorithms are presented for enhancing the performance of the suggested PID controller. These algorithms are Back-Propagation Neural Network and Particle Swarm Optimization (PSO). The performance and characteristics of DC servo motor are explained. The simulation results that obtained by using Matlab program show that the steady state error is eliminated with shorter adjusted time when using these algorithms with PID controller. A comparative between the two algorithms are described in this paper to show their effectiveness, which is found that the PSO algorithm gives be

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