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Comparison between (ARIMA) and (ANNs) models for estimating the relative humidity for Baghdad city
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The aim of the research is to study the comparison between (ARIMA) Auto Regressive Integrated Moving Average and(ANNs) Artificial Neural Networks models and to select the best one for prediction the monthly relative humidity values depending upon the standard errors between estimated and observe values . It has been noted that both can be used for estimation and the best on among is (ANNs) as the values (MAE,RMSE, R2) is )0.036816,0.0466,0.91) respectively for the best formula for model (ARIMA) (6,0,2)(6,0,1) whereas the values of estimates relative to model (ANNs) for the best formula (5,5,1) is (0.0109, 0.0139 ,0.991) respectively. so that model (ANNs) is superior than (ARIMA) in a such evaluation.

Publication Date
Wed Aug 01 2018
Journal Name
Journal Of Zankoy Sulaimani - Part A
A Comparison Study on the Formation of Administrative and Leadership Policies for the Team and Individual Olympic Games in the Iraqi National Olympic Committee
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The planning for the formation of administrative policies and guidance through leadership are important things for managing administrative processes and sporting activities. As both contribute in the stability of the administrative conditions, and their development in the sport federations, whether they both were attentive about team and individual Olympic Games. The two researchers observe that, there is a variation in the correct way of application. Particularly in the formulation of administrative policies and leadership describing it as, modern management standards for both team and individual Olympic Games in the Iraqi National Olympic Committee. That led to cause a misconception and lack of clarity for some administrators of those uni

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Publication Date
Wed Jun 15 2022
Journal Name
Malaysian Journal Of Science
STUDY THE RELATIONSHIP BETWEEN BREMSSTRAHLUNG DOSE RATE AND THE ENERGY OF BETA RAY FOR DIFFERENT TYPES OF SHIELD
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The dose rate for bremsstrahlung radiation from beta particles with energy (1.710) MeV and (2.28) MeV which comes from (32P and 90Y) beta source respectively have been calculated through six materials (polyethylene, wood, aluminum, iron, tungsten and lead) for first shielding material with thickness (x=1) mm which are putting between beta sources and second shield (polyethylene, aluminum and lead) with thickness (1, 2 &4) mm have been calculated. The distance between beta source and second shield is constant (D=1) cm. This dose rate was found by program called Rad Pro Calculator (version 3.26). The results of dose rate of beta particles were plotted as a function to the atomic number (Z) for first shield materials for each

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Publication Date
Wed Jun 15 2022
Journal Name
Malaysian Journal Of Science
STUDY THE RELATIONSHIP BETWEEN BREMSSTRAHLUNG DOSE RATE AND THE ENERGY OF BETA RAY FOR DIFFERENT TYPES OF SHIELD
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The dose rate for bremsstrahlung radiation from beta particles with energy (1.710) MeV and (2.28) MeV which comes from (32P and 90Y) beta source respectively have been calculated through six materials (polyethylene, wood, aluminum, iron, tungsten and lead) for first shielding material with thickness (x=1) mm which are putting between beta sources and second shield (polyethylene, aluminum and lead) with thickness (1, 2 &4) mm have been calculated. The distance between beta source and second shield is constant (D=1) cm. This dose rate was found by program called Rad Pro Calculator (version 3.26). The results of dose rate of beta particles were plotted as a function to the atomic number (Z) for first shield materials for each

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Publication Date
Fri Feb 28 2025
Journal Name
Energies
Synergizing Machine Learning and Physical Models for Enhanced Gas Production Forecasting: A Comparative Study of Short- and Long-Term Feasibility
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Advanced strategies for production forecasting, operational optimization, and decision-making enhancement have been employed through reservoir management and machine learning (ML) techniques. A hybrid model is established to predict future gas output in a gas reservoir through historical production data, including reservoir pressure, cumulative gas production, and cumulative water production for 67 months. The procedure starts with data preprocessing and applies seasonal exponential smoothing (SES) to capture seasonality and trends in production data, while an Artificial Neural Network (ANN) captures complicated spatiotemporal connections. The history replication in the models is quantified for accuracy through metric keys such as m

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Publication Date
Tue Jan 01 2019
Journal Name
Iop
Water cut comparison for a really similar gridding system (line drive pattern)
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Publication Date
Fri Jan 01 2021
Journal Name
International Journal Of Agricultural And Statistical Sciences
COMPARISON OF SOME NONPARAMETRIC METHODS TO DETERMINE THE NUMBER OF RADIATION DOSES FOR BREAST CANCER PATIENTS
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Radiation therapy plays an important role in improving breast cancer cases, in order to obtain an appropriateestimate of radiation doses number given to the patient after tumor removal; some methods of nonparametric regression werecompared. The Kernel method was used by Nadaraya-Watson estimator to find the estimation regression function forsmoothing data based on the smoothing parameter h according to the Normal scale method (NSM), Least Squared CrossValidation method (LSCV) and Golden Rate Method (GRM). These methods were compared by simulation for samples ofthree sizes, the method (NSM) proved to be the best according to average of Mean Squares Error criterion and the method(LSCV) proved to be the best according to Average of Mean Absolu

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Publication Date
Wed Jun 30 2021
Journal Name
Journal Of Economics And Administrative Sciences
A Comparison between robust methods in canonical correlation by using empirical influence function
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       Canonical correlation analysis is one of the common methods for analyzing data and know the relationship between two sets of variables under study, as it depends on the process of analyzing the variance matrix or the correlation matrix. Researchers resort to the use of many methods to estimate canonical correlation (CC); some are biased for outliers, and others are resistant to those values; in addition, there are standards that check the efficiency of estimation methods.

In our research, we dealt with robust estimation methods that depend on the correlation matrix in the analysis process to obtain a robust canonical correlation coefficient, which is the method of Biwe

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Publication Date
Wed Dec 01 2021
Journal Name
Computers & Electrical Engineering
Utilizing different types of deep learning models for classification of series arc in photovoltaics systems
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Publication Date
Wed Nov 05 2025
Journal Name
Irrigation And Drainage
Predicting Potential Salinity in River Water for Irrigation Water Purposes Using Integrative Machine Learning Models
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ABSTRACT<p>Accurate prediction of river water quality parameters is essential for environmental protection and sustainable agricultural resource management. This study presents a novel framework for estimating potential salinity in river water in arid and semi‐arid regions by integrating a kernel extreme learning machine (KELM) with a boosted salp swarm algorithm based on differential evolution (KELM‐BSSADE). A dataset of 336 samples, including bicarbonate, calcium, pH, total dissolved solids and sodium adsorption ratio, was collected from the Idenak station in Iran and was used for the modelling. Results demonstrated that KELM‐BSSADE outperformed models such as deep random vector funct</p> ... Show More
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Publication Date
Mon Mar 15 2021
Journal Name
Journal Of Baghdad College Of Dentistry
Comparison between the mesiodistal crown dimensions of second primary molar with stainless steel crowns from different companies
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Background: Due to the variations in tooth anatomy and size among different populations, this study aimed to compare the mesiodistal width of primary second molars in Iraqi children with the mesiodistal width of stainless-steel crowns from different companies. Materials and Methods: This cross-sectional study was conducted on 220 intact maxillary and mandibular primary second molars selected from boys and girls’ Iraqi children aged 8-9 years collected from different primary schools in Baghdad city. The mesiodistal dimensions of the selected teeth and the available maxillary and mandibular stainless-steel crowns from three different companies were measured by using a 3-D scanner, and then the whole measurements were calculated usin

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