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A Realistic Aggregate Load Representation for A Distribution Substation in Baghdad Network
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Electrical distribution system loads are permanently not fixed and alter in value and nature with time. Therefore, accurate consumer load data and models are required for performing system planning, system operation, and analysis studies. Moreover, realistic consumer load data are vital for load management, services, and billing purposes. In this work, a realistic aggregate electric load model is developed and proposed for a sample operative substation in Baghdad distribution network. The model involves aggregation of hundreds of thousands of individual components devices such as motors, appliances, and lighting fixtures. Sana’a substation in Al-kadhimiya area supplies mainly residential grade loads. Measurement-based techniques are to be used in estimating the substation load model parameters. The proposed model accounts for the effect of the feeders, the LV- transformers and the compensation devices present in the system. The model validation is evident from calculated results comparison to realistic measured data.

 

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Publication Date
Fri Jul 19 2024
Journal Name
An International Journal Of Optimization And Control: Theories & Applications (ijocta)
Design optimal neural network based on new LM training algorithm for solving 3D - PDEs
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In this article, we design an optimal neural network based on new LM training algorithm. The traditional algorithm of LM required high memory, storage and computational overhead because of it required the updated of Hessian approximations in each iteration. The suggested design implemented to converts the original problem into a minimization problem using feed forward type to solve non-linear 3D - PDEs. Also, optimal design is obtained by computing the parameters of learning with highly precise. Examples are provided to portray the efficiency and applicability of this technique. Comparisons with other designs are also conducted to demonstrate the accuracy of the proposed design.

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Publication Date
Wed Jan 01 2020
Journal Name
International Conference Of Numerical Analysis And Applied Mathematics Icnaam 2019
Functionalized multi-walled carbon nanotubes network sensor for NO2 gas detection at room temperature
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Publication Date
Mon Apr 03 2023
Journal Name
International Journal Of Online And Biomedical Engineering (ijoe)
An Integrated Grasshopper Optimization Algorithm with Artificial Neural Network for Trusted Nodes Classification Problem
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Wireless Body Area Network (WBAN) is a tool that improves real-time patient health observation in hospitals, asylums, especially at home. WBAN has grown popularity in recent years due to its critical role and vast range of medical applications. Due to the sensitive nature of the patient information being transmitted through the WBAN network, security is of paramount importance. To guarantee the safe movement of data between sensor nodes and various WBAN networks, a high level of security is required in a WBAN network. This research introduces a novel technique named Integrated Grasshopper Optimization Algorithm with Artificial Neural Network (IGO-ANN) for distinguishing between trusted nodes in WBAN networks by means of a classifica

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Publication Date
Sat Jan 01 2022
Journal Name
Aip Conference Proceedings
Artificial neural network model for predicting the desulfurization efficiency of Al-Ahdab crude oil
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Publication Date
Tue Mar 30 2021
Journal Name
Journal Of Economics And Administrative Sciences
The Bayesian Estimation for The Shape Parameter of The Power Function Distribution (PFD-I) to Use Hyper Prior Functions
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The objective of this study is to examine the properties of Bayes estimators of the shape parameter of the Power Function Distribution (PFD-I), by using two different prior distributions for the parameter θ and different loss functions that were compared with the maximum likelihood estimators. In many practical applications, we may have two different prior information about the prior distribution for the shape parameter of the Power Function Distribution, which influences the parameter estimation. So, we used two different kinds of conjugate priors of shape parameter θ of the <

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Publication Date
Wed Sep 28 2022
Journal Name
Gsc Advanced Research And Reviews
Distribution and seasonal spread of zooplankton in Iraqi waters
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A summary of zooplankton research done in Peruvian marine waters is presented. We first provide a brief overview of the evolution of zooplankton studies off Peru before reviewing zooplankton biodiversity, regional distribution, seasonal and interannual fluctuation, trophodynamics, secondary production, and modeling are some of these topics. We evaluate research on various meroplankton, macroplankton, mesoplankton, and microplankton groups and provide a list of species from both published and unpublished sources. Three regional zooplankton groups have been identified: A shelf group on the continental shelf dominated by Acartia tonsa and Centropages brachiatus; A slope group on the continental shelf with siphonophores, bivalves, foramin

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Publication Date
Thu Jun 01 2023
Journal Name
Baghdad Science Journal
Gogny interaction and nuclear charge distribution in 48Ca Nucleus
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Charge multipole Coulomb scattering form factors in 48Ca nucleus have been reproduced utilizing the theory of nuclear shell. The efficient two-body nuclear potential fpbm is considered to construct the-spin orbit term LS vectors with Harmonic Oscillator HO potential as a wave function of single particle in Fp shell. Discarded spaces ( core + higher configuration) are taken into account through the Core polarization effect by model space with accurate two-body potential of Gogny to  interact the LS operating particles with the discarded space pair ( particle-hole) with energy of excitation equal to 2ћω. Gogny interaction has been selected as it had succeeded in nuclear shell theory. The computed results were compared with th

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Publication Date
Wed Apr 01 2015
Journal Name
Al–bahith Al–a'alami
University Youth Attitudes towards Electronic Advertisements and their Relationship to the Behavior of the Consumer A Field Study of a Sample of Students of the College of Mass-Communication / University of Baghdad as a Model
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This research aims at identifying the communicative habits and content reflections on the communication process, especially the young audience which is one of the main group for whom the announcements are made. Because young people face life with passion and aspiration making them respond to each effect used by the media in the design of the advertising using all the effective techniques, attractive methods for young children like depending on drama, technical tricks, music and logos easily to be remembered and responded to the desires of the young in their entertainment. This research also aims at identifying the impact of the internet as a channel of commercial advertising on the purchasing behavior of young people at the universities

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Publication Date
Sat Dec 20 2025
Journal Name
Journal Of Baghdad College Of Dentistry
In-Vitro evaluation of load-deflection characteristics and force levels of nickel titanium orthodontic archwires
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Background: Nickel-titanium (NiTi) archwires have become increasingly popular because of their ability to release constant light forces, which are especially useful during initial alignment and leveling phase. The aim of the present study was to investigate and compare the load–deflection characteristics of four commercially available NiTi archwires. Materials and methods: 200 NiTi 0.014, 0.016, 0.018, 0.016x0.022 and 0.019x0.025-inch nickel–titanium archwires from four different manufacturers (3M, Ortho Technology, Jiscop and Astar) were tested. The load-deflection properties of these archwires were evaluated by a full arch bending test in both palatal and gingival directionsat 37°C temperature using a universal material t

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Publication Date
Fri Jan 01 2021
Journal Name
International Journal Of Agricultural And Statistical Sciences
A noval SVR estimation of figarch modal and forecasting for white oil data in Iraq
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The purpose of this paper is to model and forecast the white oil during the period (2012-2019) using volatility GARCH-class. After showing that squared returns of white oil have a significant long memory in the volatility, the return series based on fractional GARCH models are estimated and forecasted for the mean and volatility by quasi maximum likelihood QML as a traditional method. While the competition includes machine learning approaches using Support Vector Regression (SVR). Results showed that the best appropriate model among many other models to forecast the volatility, depending on the lowest value of Akaike information criterion and Schwartz information criterion, also the parameters must be significant. In addition, the residuals

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