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ijp-1015
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 atmospheric pressure were used as input parameters in order to obtain the daily average of sunshine duration (SD) as the output. The eight-year data were divided into two categories. The first category covers whole years (annually) and the second category is seasonal. To recognize and assess the influence of different input parameters on sunshine duration, six models of ANN have been evolved. The findings showed that in the annual models, the outcomes of RMSE, MAE and R for the model with input parameters (Month, Cloud Level and Average Temperature) were the best results 1.82, 1.175 and 0.89, respectively. As for the season models, the outcomes of RMSE, MAE and R for the autumn season were the best results 1.450, 1.009 and 0.94, respectively. Accordingly, the performance of the artificial neural network is considerably effective in predicting the sunshine duration.

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Publication Date
Sat Dec 02 2017
Journal Name
Al-khwarizmi Engineering Journal
Direction Finding Using GHA Neural Networks
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 This paper adapted the neural network for the estimating of the direction of arrival (DOA). It uses an unsupervised adaptive neural network with GHA algorithm to extract the principal components that in turn, are used by Capon method to estimate the DOA, where by the PCA neural network we take signal subspace only and use it in Capon (i.e. we will ignore the noise subspace, and take the signal subspace only).

 

 

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Publication Date
Thu Oct 17 2024
Journal Name
مجلة ميسان لعلوم التربية البدنية
A historical study of the origins of the sport of polo and its development from the royal court to the stadiums of modern times
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The sport of polo, the game of kings and sultans, is one of the traditional sports that has defied time throughout its long history. It has preserved its historical roots and been able to adapt to contemporary requirements, societal transformations, and temporal and spatial variables. It has moved from an aristocratic sport practiced as a form of entertainment to a professional competitive sport. It attracts many players and millions of viewers, so it is a living model of how sports develop and transform from a local tradition into global sports with organized rules managed by international institutions and with many championships worldwide. Through this, the research objectives were formulated, including exploring sports' origins. Polo in

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Publication Date
Tue Apr 01 2025
Journal Name
Journal Of Engineering
Comparative Analysis of The Combined Model (Spatial and Temporal) and Regression Models for Predicting Murder Crime
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This research dealt with the analysis of murder crime data in Iraq in its temporal and spatial dimensions, then it focused on building a new model with an algorithm that combines the characteristics associated with time and spatial series so that this model can predict more accurately than other models by comparing them with this model, which we called the Combined Regression model (CR), which consists of merging two models, the time series regression model with the spatial regression model, and making them one model that can analyze data in its temporal and spatial dimensions. Several models were used for comparison with the integrated model, namely Multiple Linear Regression (MLR), Decision Tree Regression (DTR), Random Forest Reg

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Publication Date
Thu Dec 31 2020
Journal Name
Iraqi Journal Of Market Research And Consumer Protection
ASTUDYON THERECORDOF EVALUATINGTHE SUPPLIERSACCORDING TO THE CONCEPT OF QUALITY AND BENEFITING FROM IT IN PRACTICE IN AL-FURAT STATE COMPANY AND FINDING POSSIBLE PROPOSALS FOR ITS DEVELOPMENT: ASTUDYON THERECORDOF EVALUATINGTHE SUPPLIERSACCORDING TO THE CONCEPT OF QUALITY AND BENEFITING FROM IT IN PRACTICE IN AL-FURAT STATE COMPANY AND FINDING POSSIBLE PROPOSALS FOR ITS DEVELOPMENT
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Success in selecting the best among the sources of supply is one of the most important factors in the efficiency of the procurement activity in the company, because the proper selection of the source of the supply significantly affect the achievement of what is desired by the factors of quality, quantity, price and service, and the ability of the competent supplier to meet everything associated with this Factors of commitments, hereby supporting the procurement function's efforts to fully discharge its responsibilities, and in view of adopting of Al-Furat company quality management system by applying the standards of ISO (9001: 2015) and purpose of getting the on-demand benefits from the application of international standards reg

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Publication Date
Thu Jan 01 2009
Journal Name
Computer And Information Science 2009
The Stochastic Network Calculus Methodology
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Home Computer and Information Science 2009 Chapter The Stochastic Network Calculus Methodology Deah J. Kadhim, Saba Q. Jobbar, Wei Liu & Wenqing Cheng Chapter 568 Accesses 1 Citations Part of the Studies in Computational Intelligence book series (SCI,volume 208) Abstract The stochastic network calculus is an evolving new methodology for backlog and delay analysis of networks that can account for statistical multiplexing gain. This paper advances the stochastic network calculus by deriving a network service curve, which expresses the service given to a flow by the network as a whole in terms of a probabilistic bound. The presented network service curve permits the calculation of statistical end-to-end delay and backlog bounds for broad

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Publication Date
Wed Jan 13 2016
Journal Name
University Of Baghdad
Employ Mathematical Model and Neural Networks for Determining Rate Environmental Contamination
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Publication Date
Wed Dec 01 2021
Journal Name
Baghdad Science Journal
Advanced Intelligent Data Hiding Using Video Stego and Convolutional Neural Networks
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Steganography is a technique of concealing secret data within other quotidian files of the same or different types. Hiding data has been essential to digital information security. This work aims to design a stego method that can effectively hide a message inside the images of the video file.  In this work, a video steganography model has been proposed through training a model to hiding video (or images) within another video using convolutional neural networks (CNN). By using a CNN in this approach, two main goals can be achieved for any steganographic methods which are, increasing security (hardness to observed and broken by used steganalysis program), this was achieved in this work as the weights and architecture are randomized. Thus,

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Publication Date
Sun Sep 01 2019
Journal Name
Civil Engineering Journal
Simulation and Assessment of Groundwater for Domestic and Irrigation Uses
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The alluvial fan of Mandali located between latitude 30˚45’00” N longitude 45˚30’00” E in east of Diyala Governorate, Iraq. Thirty-five wells were identified in the study area with average depth of 84 m and estimated area of 21550 ha. A three-dimensional conceptual model was prepared by using GMS program. From wells cross sections, four geological layers have been identified. The hydraulic conductivity of these layers was calculated for steady state condition, where the water levels for nine wells distributed over the study area were observed at same time. Afterward, PEST facility in the GMS was used to estimate the aquifer hydraulic characteristics. Other characteristics such as storage coefficient and specific yield have

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Publication Date
Thu Jun 01 2023
Journal Name
Baghdad Science Journal
Modeling The Power Grid Network Of Iraq
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Recently, the theory of Complex Networks gives a modern insight into a variety of applications in our life. Complex Networks are used to form complex phenomena into graph-based models that include nodes and edges connecting them. This representation can be analyzed by using network metrics such as node degree, clustering coefficient, path length, closeness, betweenness, density, and diameter, to mention a few. The topology of the complex interconnections of power grids is considered one of the challenges that can be faced in terms of understanding and analyzing them. Therefore, some countries use Complex Networks concepts to model their power grid networks. In this work, the Iraqi Power Grid network (IPG) has been modeled, visua

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Publication Date
Fri Jan 01 2021
Journal Name
Lecture Notes In Networks And Systems
Evaluating the Efficiency of Regional Transport Network
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