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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
Thu Dec 14 2023
Journal Name
Malaysian Journal Of Mathematical Sciences
The Effect of Alternative Resource and Refuge on the Dynamical Behavior of Food Chain Model
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This article examines and proposes a dietary chain model with a prey shelter and alternative food sources. It is anticipated that mid-predators' availability is positively correlated with the number of refuges. The solution's existence and exclusivity are examined. It is established that the solution is bounded. It is explored whether all potential equilibrium points exist and are locally stable. The Lyapunov approach is used to investigate the equilibrium points' worldwide stability. Utilizing a Sotomayor theorem application, local bifurcation is studied. Numerical simulation is used to better comprehend the dynamics of the model and define the control set of parameters.

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Publication Date
Wed Mar 10 2021
Journal Name
Baghdad Science Journal
On The Dynamical Behavior of a Prey-Predator Model With The Effect of Periodic Forcing
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The dynamical behavior of a two-dimensional continuous time dynamical system describing by a prey predator model is investigated. By means of constructing suitable Lyapunov functional, sufficient condition is derived for the global asymptotic stability of the positive equilibrium of the system. The Hopf bifurcation analysis is carried out. The numerical simulations are used to study the effect of periodic forcing in two different parameters. The results of simulations show that the model under the effects of periodic forcing in two different parameters, with or without phase difference, could exhibit chaotic dynamics for realistic and biologically feasible parametric values.

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Publication Date
Sat Aug 01 2020
Journal Name
Iop Conference Series: Materials Science And Engineering
Using BIM for Optimizing the Upgrading Cost to Convert the Traditional Buildings to Sustainable Buildings in Iraq
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Abstract<p>A high percentage of existing buildings in Iraq are traditional buildings, yet there is approximately no such green building in Baghdad or other governorates. Most of these buildings require urgent upgrading to increase their performance (operationally, economically, and environmentally), also the building owners looking for identifying and implementing many of the green building measures to reduce the operational and maintenance costs of their buildings. The decision-makers need to support the possibility of achieving sustainable measures of existing building rating systems such as LEED or BREEAM, and that would require an optimization model. The goal of this study is to maximize the</p> ... Show More
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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
Sun Jul 02 2017
Journal Name
Journal Of Educational And Psychological Researches
The effectiveness of instructional design according to whole brain theory of Herman in the achievement of chemistry of the fifth scientific students
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The research aimed to identify the effectiveness of instructional design according to whole brain theory of Herman in the achievement of chemistry at the fifth scientific students at a secondary school of the General Directorate for Educational in Diyala / Baladruz in Iraq. The research sample Consisted of (57 student, (29) students as experimental group studied according to instructional design strategies for whole brain theory of Herrmann and (28) a student as a control group studied by the usual way for two semesters, a prepared achievement test as article and objective type of multiple choice, the coefficient stability of alpha-Cronbach equation reached (0.86). The research Results showed the presence of a statistically significant d

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Publication Date
Mon Jan 01 2024
Journal Name
Journal Of Clinical And Experimental Dentistry
Eradication of mature biofilm from the isthmus region using Er, Cr: YSGG Laser as an activator of 2% chlorhexidine gluconate
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Publication Date
Wed Jun 24 2020
Journal Name
Bulletin Of The Iraq Natural History Museum (p-issn: 1017-8678 , E-issn: 2311-9799)
NEW DESCRIPTION OF THE LARVAL STAGE OF LATIPALPIS (PALPILATIS) JOHANIDESI NIEHUIS, 2002 (COLEOPTERA, BUPRESTIDAE) FROM ERBIL PROVINCE, KURDISTAN REGION, IRAQ
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   The present study introduced a new description of the last larval instar of the oak tree borer, Latipalpis johanidesi Niehuis, 2002 (Coleoptera, Buprestidae). The larval specimens were collected from the oak trees within the mountainous areas, Erbil governorate, Iraqi Kurdistan Region, during the beginning of April till the end of May 2019.

   Schematic sketches were provided to illustrate unclear morphological features, and the results presented importance morphological evidence for confirming the identification of this species in the larval stage precisely.

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Publication Date
Fri Oct 30 2020
Journal Name
Journal Of Economics And Administrative Sciences
Comparison between method penalized quasi- likelihood and Marginal quasi-likelihood in estimating parameters of the multilevel binary model
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Multilevel models are among the most important models widely used in the application and analysis of data that are characterized by the fact that observations take a hierarchical form, In our research we examined the multilevel logistic regression model (intercept random and slope random model) , here the importance of the research highlights that the usual regression models calculate the total variance of the model and its inability to read variance and variations between levels ,however in the case of multi-level regression models, the calculation of  the total variance is inaccurate and therefore these models calculate the variations for each level of the model, Where the research aims to estimate the parameters of this m

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Publication Date
Sun Mar 13 2011
Journal Name
Baghdad Science Journal
Phytoplankton primary production in southern Iraqi marshes after restoration
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Primary productivity and chlorophyll-a were used in this study to monitor the restoration process of southern Iraqi marshes (Al-Hewaizeh, central marshes, and Al-Hammar). The phytoplankton primary productivity was based on oxygen light/dark bottle method. Two different depths samples were taken monthly from six studied marshes stations (two stations for each marsh) during November 2005 to October 2006, while chlorophyll-a samples taken from surface water. The phytoplankton primary productivity values ranged 9.38 – 249.79 mg C/m3.hr for all marshes, its values for surface water sample ranged 11.71 – 256.24 mg C/m3.hr, while for 1m depth ranged 9.38 – 142.5 mg C/m3.hr. Chlorophyll-a values ranged between (1.1 – 21.26) µg/l indicating

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Publication Date
Tue Dec 26 2017
Journal Name
Al-khwarizmi Engineering Journal
Optimization of Wear Parameters in AISI 4340 Steel
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Abstract

 This study investigated the optimization of wear behavior of AISI 4340 steel based on the Taguchi method under various testing conditions. In this paper, a neural network and the Taguchi design method have been implemented for minimizing the wear rate in 4340 steel. A back-propagation neural network (BPNN) was developed to predict the wear rate. In the development of a predictive model, wear parameters like sliding speed, applying load and sliding distance were considered as the input model variables of the AISI 4340 steel. An analysis of variance (ANOVA) was used to determine the significant parameter affecting the wear rate. Finally, the Taguchi approach was applied to determine

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