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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
Sun Apr 02 2017
Journal Name
Journal Of Educational And Psychological Researches
Assisting Students of Al-Quds Open University to Design Computerized Lessons According to ADDIE
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This Action research aimed at Assisting Students of Faculty of Educational Sciences  at Al-Quds Open University to design computerized  lessons using the Power Point software and according to ADDIE model. The study sample consisted of 40 students  who were taking a course titled Technology of Education during the second semester of the 2014-2015 academic year and three academic instructors . To collect the required date  , the researchers used  focus group technique and structured interviews to get information from the 40 students and the three academic instructors involved in the course Technology of Education in QOU /Nablus Branch. In addition to these methods, a workshop with a guiding checklist was employed t

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Publication Date
Wed Jul 01 2020
Journal Name
Journal Of Engineering
Using Adaptive Neuro Fuzzy Inference System to Predict Rate of Penetration from Dynamic Elastic Properties
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Rate of penetration plays a vital role in field development process because the drilling operation is expensive and include the cost of equipment and materials used during the penetration of rock and efforts of the crew in order to complete the well without major problems. It’s important to finish the well as soon as possible to reduce the expenditures. So, knowing the rate of penetration in the area that is going to be drilled will help in speculation of the cost and that will lead to optimize drilling outgoings. In this research, an intelligent model was built using artificial intelligence to achieve this goal.  The model was built using adaptive neuro fuzzy inference system to predict the rate of penetration in

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Publication Date
Thu Sep 01 2022
Journal Name
Iraqi Journal Of Physics
Development and Assessment of Feed Forward Back Propagation Neural Network Models to Predict Sunshine Duration
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         The duration of sunshine is one of the important indicators and one of the variables for measuring the amount of solar radiation collected in a particular area. Duration of solar brightness has been used to study atmospheric energy balance, sustainable development, ecosystem evolution and climate change. Predicting the average values of sunshine duration (SD) for Duhok city, Iraq on a daily basis using the approach of artificial neural network (ANN) is the focus of this paper. Many different ANN models with different input variables were used in the prediction processes. The daily average of the month, average temperature, maximum temperature, minimum temperature, relative humidity, wind direction, cloud level and atmosp

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Publication Date
Tue Jan 25 2022
Journal Name
Iraqi Journal Of Science
Estimation the best areas of Sun duration hours in Iraq by applying IDW type of interpolation techniques by using GIS program
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In this paper solar radiation was studied over the Iraqi countary land. The best sun duration hours regions (maximum hours) in Iraq were estimated detected by using Geographic information system (GIS Ver. 9.2) program to apply the (Inverse distance weighting) IDW exact interpolation technique depending on the measured data of metrological stations were distributed on the land areas of Iraq. The total area of the best regions was calculated .Excel 2007 program is used in calculation, graphics and comparison the results.

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Publication Date
Wed Aug 31 2022
Journal Name
Iraqi Journal Of Science
Biodiversity and Structure of Rotifera Communities in the Great Garraf Drain Channel, Southern Iraq
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     Three sites, selected on the Great Garraf Drain Channel (GGDC) demonstrated the first ever study dealing with rotifers biodiversity features from August 2019 till July 2020. Seventy-two taxonomic units were identified. The high densities of rotifera ranged from 733.32 - 32300 Ind./m3. Brachionus urceolaris, Keratella quadrata (long spin), Keratella quadrata (short spin) and Syncheta obloga were the most common relative abundance recorded in the index. In contrast the results of the constant index showed that there were nine constant taxonomic units. The species richness index was recorded from 1.489- 6.900. Jaccard presence similarity index revealed a strong link between stations 2

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Publication Date
Thu Jun 30 2022
Journal Name
Iraqi Journal Of Science
Biostratigraphy of the Early Cretaceous Mauddud Formation in Ratawi Oilfield, Basrah Governorate, Southern Iraq
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      The biostratigraphy of the Early Cretaceous Mauddud Formation was studied in the Ratawi Oilfield, Basra Governorate, southern Iraq, using integrated borehole data set (core and cutting samples and well logs) in two drilled wells to analyze the biostratigraphy of the formation.  One hundred eighty-three slides for both selected wells were investigated. The formation is composed of light grey dolomitized limestone and pseudo-oolitic creamy limestone with green to bluish shale. Three biozones were discriminated, these are: Orbitolina qatarica range zone; Orbitolina sefini range zone and Orbitolina concava range zone. The age of these biozones extends to include the Late Albian (Orbitolina qatarica<

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Publication Date
Wed Mar 30 2022
Journal Name
Iraqi Journal Of Science
Current Potential Options for COVID-19 Treatment in Iraq- Kurdistan Region and the Rest of the World: A Mini-review
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    COVID-19 is an infectious pandemic disease which is caused by the severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2). Up to date, scientists are trying to identify a new specific antiviral drug to overcome this disease. Different methods are under study and evaluation in the entire world to control the virus, including blood plasma, blood purification, and antimicrobial and antiviral agents; however, there are no approved drugs yet. This review is focused on the conducted clinical trials worldwide, including the Iraq- Kurdistan region, China, USA, and Europe, to fi

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Publication Date
Sat Oct 20 2018
Journal Name
Journal Of Economics And Administrative Sciences
Bayesian Tobit Quantile Regression Model Using Four Level Prior Distributions
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Abstract:

      In this research we discussed the parameter estimation and variable selection in Tobit quantile regression model in present of multicollinearity problem. We used elastic net technique as an important technique for dealing with both multicollinearity and variable selection. Depending on the data we proposed Bayesian Tobit hierarchical model with four level prior distributions . We assumed both tuning parameter are random variable and estimated them with the other unknown parameter in the model .Simulation study was used for explain the efficiency of the proposed method and then we compared our approach with (Alhamzwi 2014 & standard QR) .The result illustrated that our approach

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Publication Date
Fri Dec 24 2021
Journal Name
Iraqi Journal Of Science
Best Regression for Eye Recognition
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     Human eye offers a number of opportunities for biometric recognition. The essential parts of the eye like cornea, iris, veins and retina can determine different characteristics. Systems using eyes’ features are widely deployed for identification in government requirement levels and laws; but also beginning to have more space in portable validation world.

The first image was prepared to be used and monitored using CLAHE which means (Contrast Limited Adaptive Histogram Equalization) to improve the contrast of the image, after that the 3D surfac

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Publication Date
Wed Aug 01 2018
Journal Name
Journal Of Economics And Administrative Sciences
Analysis the Relationship between the Standards of Credit Assessment and Non-Performing Loans at the Gulf Commercial Bank
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This paper aims to identify the approaches used in assessment the credit applications by Iraqi banks, as well as which approach is most used. It also attempted to link these approaches with reduction of credit default and banks’ efficiency particularly for the Gulf Commercial Bank. The paper found that the Gulf Bank widely relies on the method of Judgment Approach for assessment the credit applications in order to select the best of them with low risk of default. In addition, the paper found that the method of Judgment Approach was very important for the Gulf Bank and it driven in reduction the ratio of credit default as percentage of total credit. However, it is important to say that the adoption of statistical approaches for

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