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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
Wed Mar 15 2023
Journal Name
Al-academy
Active design and its principles in industrial product design
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 The problem of the research came through the following question (what is the effectiveness of active design in contemporary industrial products), and it emphasized the importance of research to make society with its members in a positive state of activity, and what can help the industrial product design to achieve this, but the goal of the study is (determining the characteristics and principles of design Active and its effectiveness in the industrial product), and the study was determined by industrial products related to daily, recreational and sports activity, The researcher relied on a form to determine the axes of analysis for the sample models, in order to reach the results of the research, the most important of which are: Realiz

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Publication Date
Fri Apr 30 2021
Journal Name
Eastern-european Journal Of Enterprise Technologies
Implementation of artificial neural network to achieve speed control and power saving of a belt conveyor system
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According to the importance of the conveyor systems in various industrial and service lines, it is very desirable to make these systems as efficient as possible in their work. In this paper, the speed of a conveyor belt (which is in our study a part of an integrated training robotic system) is controlled using one of the artificial intelligence methods, which is the Artificial Neural Network (ANN). A visions sensor will be responsible for gathering information about the status of the conveyor belt and parts over it, where, according to this information, an intelligent decision about the belt speed will be taken by the ANN controller. ANN will control the alteration in speed in a way that gives the optimized energy efficiency through

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Publication Date
Sun Dec 30 2018
Journal Name
Journal Of Pure And Applied Microbiology
Mixture Design of Experiments for the Optimization of Carbon Source for Promoting Undecylprodigiosin and Actinorhodin Production
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Publication Date
Sun Dec 30 2007
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Prediction of Fractional Hold-Up in RDC Column Using Artificial Neural Network
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In the literature, several correlations have been proposed for hold-up prediction in rotating disk contactor. However,
these correlations fail to predict hold-up over wide range of conditions. Based on a databank of around 611
measurements collected from the open literature, a correlation for hold up was derived using Artificial Neiral Network
(ANN) modeling. The dispersed phase hold up was found to be a function of six parameters: N, vc , vd , Dr , c d m / m ,
s . Statistical analysis showed that the proposed correlation has an Average Absolute Relative Error (AARE) of 6.52%
and Standard Deviation (SD) 9.21%. A comparison with selected correlations in the literature showed that the
developed ANN correlation noticeably

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Publication Date
Mon Mar 31 2025
Journal Name
Iraqi Statisticians Journal
Hypothesis Testing for Non-Normal Multiple Compact Regression Model
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Generalized multivariate transmuted Bessel distribution belongs to the family of probability distributions with a symmetric heavy tail. It is considered a mixed continuous probability distribution. It is the result of mixing the multivariate Gaussian mixture distribution with the generalized inverse normal distribution. On this basis, the paper will study a multiple compact regression model when the random error follows a generalized multivariate transmuted Bessel distribution. Assuming that the shape parameters are known, the parameters of the multiple compact regression model will be estimated using the maximum likelihood method and Bayesian approach depending on non-informative prior information. In addition, the Bayes factor was used

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Publication Date
Sat Jan 02 2021
Journal Name
The International Journal Of Nonlinear Analysis And Application
Atan regularized for the high dimensional Poisson regression model
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Variable selection in Poisson regression with high dimensional data has been widely used in recent years. we proposed in this paper using a penalty function that depends on a function named a penalty. An Atan estimator was compared with Lasso and adaptive lasso. A simulation and application show that an Atan estimator has the advantage in the estimation of coefficient and variables selection.

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Publication Date
Sun Jul 09 2023
Journal Name
Journal Of Engineering
1-DOF Model for Fluid-Structure-Interaction Vibration Analysis
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In this paper an attempt to provide a single degree of freedom lumped model for fluid structure interaction (FSI) dynamical analysis will be presented. The model can be used to clarify some important concept in the FSI dynamics such as the added mass, added stiffness, added damping, wave coupling ,influence mass coefficient and critical fluid depth . The numerical results of the model show that the natural frequency decrease with the increasing of many parameters related to the structure and the fluid .It is found that the interaction phenomena can become weak or strong depending on the depth of the containing fluid .The damped and un damped free response are plotted in time domain and phase plane for different model parameters It is fou

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Publication Date
Sat Aug 01 2020
Journal Name
Iop Conference Series: Materials Science And Engineering
Employ 6D-BIM Model Features for Buildings Sustainability Assessment
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Abstract<p>To translate sustainable concepts into sustainable structure, there is a require a collaborative work and technology to be innovated, such as BIM, to connect and organize different levels of industry e.g. decision-makers, contractors, economists, architects, urban planners, construction supplies and a series of urban planning and strategic infrastructure for operate, manage and maintain the facilities. This paper will investigate the BIM benefits as a project management tool, its effectiveness in sustainable decision making, also the benefit for the local industry key stakeholders by encouraging the BIM use as a project management tool to produce a sustainable building project. This p</p> ... Show More
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Publication Date
Thu Jun 29 2023
Journal Name
Wasit Journal For Pure Sciences
Suitable Methods for Solving COVID-19 Model in Iraq
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Because the Coronavirus epidemic spread in Iraq, the COVID-19 epidemic of people quarantined due to infection is our application in this work. The numerical simulation methods used in this research are more suitable than other analytical and numerical methods because they solve random systems. Since the Covid-19 epidemic system has random variables coefficients, these methods are used. Suitable numerical simulation methods have been applied to solve the COVID-19 epidemic model in Iraq. The analytical results of the Variation iteration method (VIM) are executed to compare the results. One numerical method which is the Finite difference method (FD) has been used to solve the Coronavirus model and for comparison purposes. The numerical simulat

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Publication Date
Sat May 01 2021
Journal Name
Journal Of Physics: Conference Series
Runge-kutta Numerical Method for Solving Nonlinear Influenza Model
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Abstract<p>The main object of this study is to solve a system of nonlinear ordinary differential equations (ODE) of the first order governing the epidemic model using numerical methods. The application under study is a mathematical epidemic model which is the influenza model at Australia in 1919. Runge-kutta methods of order 4 and of order 45 for solving this initial value problem(IVP) problem have been used. Finally, the results obtained have been discussed tabularly and graphically.</p>
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