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Determine the best model to predict the consumption of electric energy in the southern region
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Abstract:          

                Interest in the topic of prediction has increased in recent years and appeared modern methods such as Artificial Neural Networks models, if these methods are able to learn and adapt self with any model, and does not require assumptions on the nature of the time series. On the other hand, the methods currently used to predict the classic method such as Box-Jenkins may be difficult to diagnose chain and modeling because they assume strict conditions.

               So there was a need to compare the traditional methods used to predict the time chained with neural networks method to find the most efficient method to predict, and this is the purpose of this study.

              Contributes to predict future demand for electricity in the electric power sector to solve problems through future planning to meet changes in the demand for electricity increases. Experience has shown there is no way of certain predict appropriate for all cases, but that in each case the way of a private predict is needed to find and use. However, taking more than one way may lead to raising the future accuracy of the estimates.

               The present study aims to shed light on some of the statistical methods used to predict future demand for electricity for the Southern District, as well as a reference to more accurate methods to predict the future of energy. It has been used a number of methods to predict , such as econometric modeling technique, style and Box- Jenkins method of artificial neural network. And service to the goal of the study, which is based upon the premise that search: the neural network models more accurate than traditional models in long-term. As it is the most efficient and more accurate than other conventional models in dealing with non-linear time-series data.

                We have been using the annual electrical energy consumption data for the Southern District to conduct a comparison of the program through the application of SPSS and Minitab for statistical analysis, and Matlab language has been used to build a program in neural networks, and through the practical application it was found that neural networks gives better results and more efficient than the classic way.

 

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Publication Date
Mon Aug 01 2022
Journal Name
Baghdad Science Journal
A Case control study to determine Macrophage migration inhibitor, and N-telopeptides of type I bone collagen Levels in the sera of osteoporosis patients
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This study focused on determining the markers of Macrophage migration inhibitor (MIF), as well as the N-telopeptides of type I bone collagen (NTX), and some other parameters (alkaline phosphatase (ALP), vitamin D (Vit D), calcium (Ca), phosphorus (P), and magnesium (Mg), and their correlation with other parameters in osteoporosis. One hundred ten subjects were involved in the current study. There were two groups of patients: group I (30) women with severe osteoporosis and group II (30) women with mild osteoporosis. For comparison, 50 apparently healthy individuals were included as a control. Serum levels of MIF, and NTX were significantly higher in groups I and II as compared to the control group, which indicate that these two parameters

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Publication Date
Fri Mar 29 2024
Journal Name
Iraqi Journal Of Science
The Simulation Technique to Estimate the Parameters of Generalized Exponential Rayleigh Model
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     The paper shows how to estimate the three parameters of the generalized exponential Rayleigh distribution by utilizing the three estimation methods, namely, the moment employing estimation method (MEM), ordinary least squares estimation method (OLSEM),  and maximum entropy estimation method (MEEM). The simulation technique is used for all these estimation methods to find the parameters for the generalized exponential Rayleigh distribution. In order to find the best method, we use the mean squares error criterion. Finally, in order to extract the experimental results, one of object oriented programming languages visual basic. net was used

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Publication Date
Wed Jan 30 2019
Journal Name
Journal Of The College Of Education For Women
Identify indicators of climate change through the analysis of the amount of rain in Iraq
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United nation determined many basic climatic effects which affect the crust of Earth.
And the most important one is the climatic change and its effect on environmental, economic,
social, and political effects. So, the amount of rain which is considered as one of climatic
changes in Iraq should be studied.So, this research explains the factors which affect rain, its
overall average, the variation in the amounts of rain, the amount of yearly rain and variation
in both yearly and monthly rains by using standard variation and yearly fluctuation.As a
result, it is concluded that the number of rainy days doesn't mean an increase in rains amount.
And there's variation in rains amount in all study areas which is contrastive

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Publication Date
Fri Oct 30 2020
Journal Name
Journal Of Economics And Administrative Sciences
Institutional Performance Assessment using a model of the European Foundation for Quality Management (EFQM) A case study at an organization
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The study aims to use the European Excellence Model (EFQM) in assessing the institutional performance of the National Center for Administrative Development and Information Technology in order to determine the gap between the actual reality of the performance of the Center and the standards adopted in the model, in order to know the extent to which the Center seeks to achieve excellence in performance to improve the level of services provided and the adoption of methods Modern and contemporary management in the evaluation of its institutional performance.

The problem of the study was the absence of an institutional performance evaluation system at the centre whereby weaknesses (areas of improvement) and st

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Publication Date
Fri Mar 01 2024
Journal Name
Baghdad Science Journal
Deep Learning Techniques in the Cancer-Related Medical Domain: A Transfer Deep Learning Ensemble Model for Lung Cancer Prediction
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Problem: Cancer is regarded as one of the world's deadliest diseases. Machine learning and its new branch (deep learning) algorithms can facilitate the way of dealing with cancer, especially in the field of cancer prevention and detection. Traditional ways of analyzing cancer data have their limits, and cancer data is growing quickly. This makes it possible for deep learning to move forward with its powerful abilities to analyze and process cancer data. Aims: In the current study, a deep-learning medical support system for the prediction of lung cancer is presented. Methods: The study uses three different deep learning models (EfficientNetB3, ResNet50 and ResNet101) with the transfer learning concept. The three models are trained using a

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Publication Date
Thu Mar 01 2012
Journal Name
Journal Of Economics And Administrative Sciences
The Absorptive Capacity of Operational Budget and Monetary Policy Fiscal Cost
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In light of the enquiry raised by the Economist Mary Finn in 1995 concluding that high utilization in absorptive capacity of the economy is of inflationary tendency for industrial countries due to the equality between high rates of utilization of absorptive capacity and resource – shortage conditions leading to price inflation, the same idea was used to prove that budget utilization of operational costs and elevating absorptive capacity at the expense of investment budget leads to inflationary tendency that becomes a burden on financing the step- in policy of the Central bank to control prices through its foreign currency reserves at a time when the economy turned  into an importer of non- tradable goods and being subject

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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
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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

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Publication Date
Wed Jan 08 2025
Journal Name
Journal Of Al-rafidain University College For Sciences ( Print Issn: 1681-6870 ,online Issn: 2790-2293 )
Utilizing the Error Correction Model to Investigate the Impact of Fluctuations in Bank Deposits on the Money Supply
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This paper assesses the impact of changes and fluctuations in bank deposits on the money supply in Iraq. Employing  the research constructs an Error Correction Model (ECM) using  monthly time series data from 2010 to 2015. The analysis begins with  the Phillips-Perron unit root test to ascertain the stationarity of the  time series and the Engle and Granger cointegration test to examine  the existence of a long-term relationship. Nonparametric regression functions are estimated using two methods: Smoothing Spline and M-smoothing. The results indicate that the  M-smoothing approach is the most effective, achieving the shortest adjustment period and the highest adjustment ratio for short-term disturbances, thereby facilitating a return

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Publication Date
Thu Jan 01 2015
Journal Name
Egyptian Journal Of Aquatic Research
Ecological factors affecting the distribution of the zooplankton community in the Tigris River at Baghdad region, Iraq
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Publication Date
Fri Dec 01 2023
Journal Name
Case Studies In Chemical And Environmental Engineering
Treatment of petroleum refinery wastewater by an innovative electro-Fenton system: Performance and specific energy consumption evaluation
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