Preferred Language
Articles
/
DxenW5IBVTCNdQwC2K3g
Intelligence framework dust forecasting using regression algorithms models
...Show More Authors

<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>

Scopus Crossref
View Publication
Publication Date
Sat Oct 28 2023
Journal Name
Baghdad Science Journal
A Comparative Study on Association Rule Mining Algorithms on the Hospital Infection Control Dataset
...Show More Authors

Administrative procedures in various organizations produce numerous crucial records and data. These
records and data are also used in other processes like customer relationship management and accounting
operations.It is incredibly challenging to use and extract valuable and meaningful information from these data
and records because they are frequently enormous and continuously growing in size and complexity.Data
mining is the act of sorting through large data sets to find patterns and relationships that might aid in the data
analysis process of resolving business issues. Using data mining techniques, enterprises can forecast future
trends and make better business decisions.The Apriori algorithm has bee

... Show More
View Publication Preview PDF
Scopus (4)
Crossref (5)
Scopus Crossref
Publication Date
Tue Jul 20 2021
Journal Name
Polymer Bulletin
Influence methods of preparation on the thermal stability of polyimide/silica dust
...Show More Authors

View Publication
Scopus (29)
Crossref (25)
Scopus Clarivate Crossref
Publication Date
Tue Oct 12 2021
Journal Name
Engineering, Technology &amp; Applied Science Research
The Effect of Nanomaterials on the Properties of Limestone Dust Green Concrete
...Show More Authors

Portland cement is considered the most involved product in environmental pollution. It is responsible for about 10% of global CO2 emissions [1]. Limestone dust is a by-product of limestone plants and it is produced in thousands of tons annually as waste material. To fulfill sustainability requirements, concrete production is recommended to reduce Portland cement usage with the use of alternative or waste materials. The production of sustainable high strength concrete by using nanomaterials is one of the aims of this study. Limestone dust in 12, 16, and 20% by weight of cement replaced cement in this study. The study was divided into two parts: the first was devoted to the investigation of the best percentage of replacement of waste

... Show More
View Publication
Crossref (10)
Crossref
Publication Date
Fri Jan 01 2021
Journal Name
International Journal Of Agricultural And Statistical Sciences
A noval SVR estimation of figarch modal and forecasting for white oil data in Iraq
...Show More Authors

The purpose of this paper is to model and forecast the white oil during the period (2012-2019) using volatility GARCH-class. After showing that squared returns of white oil have a significant long memory in the volatility, the return series based on fractional GARCH models are estimated and forecasted for the mean and volatility by quasi maximum likelihood QML as a traditional method. While the competition includes machine learning approaches using Support Vector Regression (SVR). Results showed that the best appropriate model among many other models to forecast the volatility, depending on the lowest value of Akaike information criterion and Schwartz information criterion, also the parameters must be significant. In addition, the residuals

... Show More
View Publication Preview PDF
Scopus
Publication Date
Mon Feb 04 2019
Journal Name
Iraqi Journal Of Physics
Evaluated the level density for proton induced nuclear resonances in (P+48Ti) reaction using different models
...Show More Authors

The experimental proton resonance data for the reaction P+48Ti have been used to calculate and evaluate the level density by employed the Gaussian Orthogonal Ensemble, GOE version of RMT, Constant Temperature, CT and Back Shifted Fermi Gas, BSFG models at certain spin-parity and at different proton energies. The results of GOE model are found in agreement with other, while the level density calculated using the BSFG Model showed less values with spin dependence more than parity, due the limitation in the parameters (level density parameter, a, Energy shift parameter, E1and spin cut off parameter, σc). Also, in the CT Model the level density results depend mainly on two parameters (T and ground state back shift energy, E0), which are app

... Show More
View Publication Preview PDF
Crossref
Publication Date
Mon Mar 29 2021
Journal Name
Journal Of Engineering
Numerical Simulation of Water Distribution with Uptake Root in Drip Irrigation using Different Soil Hydraulic Models
...Show More Authors

Surface drip irrigation is one of the most conservative irrigation techniques that help control providing water directly on the soil through the emitters. It can supply fertilizer and providing water directly to plant roots by drippers. One of the essential needs for trickle irrigation nowadays is to obtain more knowledge about the moisture pattern under the trickling source for various types of soil with various discharge levels with trickle irrigation. Simulation numerical using HYDRUS-2D software, version 2.04 was used to estimate an equation for the wetted area from a single surface drip irrigation in unsaturated soil is taking into account water uptake by roots. In this paper, using two soil types were used, namely

... Show More
View Publication Preview PDF
Crossref
Publication Date
Sat Jan 01 2022
Journal Name
The International Journal Of Nonlinear Analysis And Applications
Developing Bulk Arrival Queuing Models with Constant Batch Policy Under Uncertainty Data Using (0-1) Variables
...Show More Authors

This paper delves into some significant performance measures (PMs) of a bulk arrival queueing system with constant batch size b, according to arrival rates and service rates being fuzzy parameters. The bulk arrival queuing system deals with observation arrival into the queuing system as a constant group size before allowing individual customers entering to the service. This leads to obtaining a new tool with the aid of generating function methods. The corresponding traditional bulk queueing system model is more convenient under an uncertain environment. The α-cut approach is applied with the conventional Zadeh's extension principle (ZEP) to transform the triangular membership functions (Mem. Fs) fuzzy queues into a family of conventional b

... Show More
Publication Date
Mon Mar 03 2025
Journal Name
Internationaljournalof Economicsandfinancestudies
CROSS-SECTIONAL REGRESSION WITH PROXIES: A SEMI-PARAMETRIC METHOD
...Show More Authors

This study investigates asset returns within the Iraq Stock Exchange by employing both the Fama-MacBeth regression model and the Fama-French three-factor model. The research involves the estimation of cross-sectional regressions wherein model parameters are subject to temporal variation, and the independent variables function as proxies. The dataset comprises information from the first quarter of 2010 to the first quarter of 2024, encompassing 22 publicly listed companies across six industrial sectors. The study explores methodological advancements through the application of the Single Index Model (SIM) and Kernel Weighted Regression (KWR) in both time series and cross-sectional analyses. The SIM outperformed the K

... Show More
View Publication
Scopus
Publication Date
Fri Oct 01 2010
Journal Name
Iraqi Journal Of Physics
Statistical Fluctuations of Energy Spectrum, Electromagnetic Transitions and Electromagnetic Moments in 136Xe Nucleus Using the Framework of Nuclear Shell Model
...Show More Authors

The fluctuation properties of energy spectrum, electromagnetic transition intensities and electromagnetic moments in nucleus are investigated with realistic shell model calculations. We find that the spectral fluctuations of are consistent with the Gaussian orthogonal ensemble of random matrices. Besides, we observe a transition from an order to chaos when the excitation energy is increased and a clear quantum signature of the breaking of chaoticity when the single-particle energies are increased. The distributions of the transition intensities and of the electromagnetic moments are well described by a Porter-Thomas distribution. The statistics of electromagnetic transition intensities clearly deviate from a Porter-Thomas distribution (i

... Show More
View Publication Preview PDF
Publication Date
Thu Jan 01 2015
Journal Name
International Journal Of Optics And Applications
Modeling and Analysis of a Miniaturized Ring Modulator Using Silicon-Polymer-Metal Hybrid Plasmonic Phase Shifter. Part I: Theoretical Framework
...Show More Authors

This paper presents comprehensive analysis and investigation for 1550nm and 1310nm ring optical modulators employing an electro-optic polymer infiltrated silicon-plasmonic hybrid phase shifter. The paper falls into two parts which introduce a theoretical modeling framework and performance assessment of these advanced modulators, respectively. In this part, analytical expressions are derived to characterize the coupling effect in the hybrid phase shifter, transmission function of the modulator, and modulator performance parameters. The results can be used as a guideline to design compact and wideband optical modulators using plasmonic technology

View Publication