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A Neural Networks based Predictive Voltage-Tracking Controller Design for Proton Exchange Membrane Fuel Cell Model
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In this work, a new development of predictive voltage-tracking control algorithm for Proton Exchange Membrane Fuel Cell (PEMFCs) model, using a neural network technique based on-line auto-tuning intelligent algorithm was proposed. The aim of proposed robust feedback nonlinear neural predictive voltage controller is to find precisely and quickly the optimal hydrogen partial pressure action to control the stack terminal voltage of the (PEMFC) model for N-step ahead prediction. The Chaotic Particle Swarm Optimization (CPSO) implemented as a stable and robust on-line auto-tune algorithm to find the optimal weights for the proposed predictive neural network controller to improve system performance in terms of fast-tracking desired voltage and less energy consumption through investigating and comparing under random current variations with the minimum number of fitness evaluation less than 20 iterations.

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Publication Date
Sun Dec 01 2019
Journal Name
Journal Of Economics And Administrative Sciences
The causal relationship between inflation and the volume of private sector deposits and the Amman Stock Exchange Index. (The case of Jordan for the period 1999-2017)
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        The study aims to show the correlation between inflation rates and the volume of private sector deposits in Jordan on one hand, and Amman Stock Exchange index for the period of 1999-2017. The study used the “Vector Auto Regression” model. Different types of tests are used such as: The “Johansen Co integration” test of joint integration, “Granger causality” test, the “Analysis of Variance Decomposition”, and “Impulse response Function” test.

The results showed there is a positive-one-way causal effect from Amman Stock Exchange index to inflation. Also, a one-way causal effect that comes from Amman Stock Exchange index to the size of private sec

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Publication Date
Wed Mar 20 2019
Journal Name
Al-khwarizmi Engineering Journal
Design and Simulation of Closed Loop Proportional Integral (PI) Controlled Boost Converter and 3-phase Inverter for Photovoltaic (PV) Applications
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This research deals with the design and simulation of a solar power system consisting of a KC200GT solar panel, a closed loop boost converter and a three phase inverter by using Matlab / Simulink. The mathematical equations of the solar panel design are presented. The electrical characteristics of the panel are tested at the values ​​of 1000  for light radiation and 25 °C for temperature environment. The Proportional Integral (PI) controller is connected   as feedback with the Boost converter to obtain a stable output voltage by reducing the oscillations in the voltage to charge a battery connected to the output of the converter. Two methods (Particle Swarm Optimization (PSO) and Zeigler- Nichols) are used for tuning

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Publication Date
Sat Jun 15 2019
Journal Name
Journal Of Baghdad College Of Dentistry
Evaluation of the effectiveness of using platelet rich fibrin (PRF) as a sole grafting material and membrane in augmentation of dehiscence and fenestration defects encountered during dental implant surgery
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Background: Bone regeneration in dehiscence and fenestration defect can be improved with the use of platelet rich fibrin (PRF) that provides a scaffold for new bone regeneration. This study was conducted to assess the effectiveness of PRF as a graft material and membrane in dehiscence and fenestration defects. Materials and Methods: This prospective clinical study included patients who received dental implants that demonstrated peri-implant defects which were augmented using Leukocyte- PRF (L-PRF) or Advanced-PRF (A-PRF). Twenty four weeks postoperatively the defect resolution and the density of regenerated bone were assessed by CBCT and re-entry surgery. The assessment also included measurement of primary and secondary implant stability

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Publication Date
Sun Dec 31 2006
Journal Name
Journal Of Engineering
Theoretical Simulation Of Stress-Strain Relations For Some Iraqiclays Using The Endochronic Model
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Publication Date
Wed Jun 27 2018
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Building Geological Model for Tertiary Reservoir of Exploration Ismail Oil Field, North Iraq
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Geologic modeling is the art of constructing a structural and stratigraphic model of a reservoir from analyses and interpretations of seismic data, log data, core data, etc. ‎[1].

   A static reservoir model typically involves four main stages, these stages are Structural modeling, Stratigraphic modeling, Lithological modeling and Petrophysical modeling ‎[2].

   Ismail field is exploration structure, located in the north Iraq, about 55 km north-west of Kirkuk city, to the north-west of the Bai Hassan field, the distance between the Bai Hassan field and Ismael field is about one kilometer ‎[3].

   Tertiary period reservoir sequences (Main Limestone), which comprise many economica

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Publication Date
Tue May 01 2012
Journal Name
2012 Second International Conference On Digital Information And Communication Technology And It's Applications (dictap)
The compact Genetic Algorithm for likelihood estimator of first order moving average model
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Recently Genetic Algorithms (GAs) have frequently been used for optimizing the solution of estimation problems. One of the main advantages of using these techniques is that they require no knowledge or gradient information about the response surface. The poor behavior of genetic algorithms in some problems, sometimes attributed to design operators, has led to the development of other types of algorithms. One such class of these algorithms is compact Genetic Algorithm (cGA), it dramatically reduces the number of bits reqyuired to store the poulation and has a faster convergence speed. In this paper compact Genetic Algorithm is used to optimize the maximum likelihood estimator of the first order moving avergae model MA(1). Simulation results

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Publication Date
Mon Mar 16 2026
Journal Name
Misan Journal Of Academic Studies
Some of Parametric and Non Parametric Estimations for Circular Regression Model via Simulation
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Circular data (circular sightings) are periodic data and are measured on the unit's circle by radian or grades. They are fundamentally different from those linear data compatible with the mathematical representation of the usual linear regression model due to their cyclical nature. Circular data originate in a wide variety of fields of scientific, medical, economic and social life. One of the most important statistical methods that represents this data, and there are several methods of estimating angular regression, including teachers and non-educationalists, so the letter included the use of three models of angular regression, two of which are teaching models and one of which is a model of educators. ) (DM) (MLE) and circular shrinkage mod

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Publication Date
Sun Mar 01 2015
Journal Name
Journal Of Engineering
Multi-Sites Multi-Variables Forecasting Model for Hydrological Data using Genetic Algorithm Modeling
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A two time step stochastic multi-variables multi-sites hydrological data forecasting model was developed and verified using a case study. The philosophy of this model is to use the cross-variables correlations, cross-sites correlations and the two steps time lag correlations simultaneously, for estimating the parameters of the model which then are modified using the mutation process of the genetic algorithm optimization model. The objective function that to be minimized is the Akiake test value. The case study is of four variables and three sites. The variables are the monthly air temperature, humidity, precipitation, and evaporation; the sites are Sulaimania, Chwarta, and Penjwin, which are located north Iraq. The model performance was

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Publication Date
Fri Sep 30 2022
Journal Name
Journal Of Economics And Administrative Sciences
Semi parametric Estimators for Quantile Model via LASSO and SCAD with Missing Data
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In this study, we made a comparison between LASSO & SCAD methods, which are two special methods for dealing with models in partial quantile regression. (Nadaraya & Watson Kernel) was used to estimate the non-parametric part ;in addition, the rule of thumb method was used to estimate the smoothing bandwidth (h). Penalty methods proved to be efficient in estimating the regression coefficients, but the SCAD method according to the mean squared error criterion (MSE) was the best after estimating the missing data using the mean imputation method

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Publication Date
Wed Apr 01 2020
Journal Name
Civil Engineering Journal
Model Development for the Prediction of the Resilient Modulus of Warm Mix Asphalt
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Increasing material prices coupled with the emission of hazardous gases through the production and construction of Hot Mix Asphalt (HMA) has driven a strong movement toward the adoption of sustainable construction technology. Warm Mix Asphalt (WMA) is considered relatively a new technology, which enables the production and compaction of asphalt concrete mixtures at temperatures 15-40 °C lower than that of traditional hot mix asphalt. The Resilient modulus (Mr) which can be defined as the ratio of axial pulsating stress to the corresponding recoverable strain, is used to evaluate the relative quality of materials as well as to generate input for pavement design or pavement evaluation and analysis. Based on the aforementioned preface, it is

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