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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
Tue May 01 2018
Journal Name
Journal Of Physics: Conference Series
Design of Light Trapping Solar Cell System by Using Zemax Program
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Publication Date
Thu Dec 08 2022
Journal Name
International Journal Of Interactive Mobile Technologies (ijim)
Implementation of RWP and Gauss Markov Mobility Model for Multi-UAV Networks in Search and Rescue Environment
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Future generations of wireless networks are expected to heavily rely on unmanned aerial vehicles (UAVs). UAV networks have extraordinary features like high mobility, frequent topology change, tolerance to link failure, and extending the coverage area by adding external UAVs. UAV network provides several advantages for civilian, commercial, search and rescue applications. A realistic mobility model must be used to assess the dependability and effectiveness of UAV protocols and algorithms.  In this research paper, the performance of the Gauss Markov (GM) and Random Waypoint (RWP) mobility models in multi-UAV networks for a search and rescue scenario is analyzed and evaluated. Additionally, the two mobility models GM and RWP are descr

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Publication Date
Fri Oct 07 2016
Journal Name
Fourth International Conference On Wireless And Optical Communications, 2016, Beijing, China
ESAM: Endocrine inspired Sensor Activation Mechanism for multi-target tracking in WSNs
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Target tracking is a significant application of wireless sensor networks (WSNs) in which deployment of self-organizing and energy efficient algorithms is required. The tracking accuracy increases as more sensor nodes are activated around the target but more energy is consumed. Thus, in this study, we focus on limiting the number of sensors by forming an ad-hoc network that operates autonomously. This will reduce the energy consumption and prolong the sensor network lifetime. In this paper, we propose a fully distributed algorithm, an Endocrine inspired Sensor Activation Mechanism for multi target-tracking (ESAM) which reflecting the properties of real life sensor activation system based on the information circulating principle in the endocr

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Publication Date
Mon Sep 01 2014
Journal Name
19th International Conference On Methods And Models In Automation And Robotics (mmar) 2014
A PSO-optimized type-2 fuzzy logic controller for navigation of multiple mobile robots
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Publication Date
Thu Mar 06 2025
Journal Name
Aip Conference Proceedings
Solving 5th order nonlinear 4D-PDEs using efficient design of neural network
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Publication Date
Fri Jan 17 2025
Journal Name
Iraqi Journal For Electrical And Electronic Engineering
Optimal Hybrid Fuzzy PID for Pitch Angle Controller in Horizontal AxisWind Turbines
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Wind turbine (WT) is now a major renewable energy resource used in the modern world. One of the most significant technologies that use the wind speed (WS) to generate electric power is the horizontal-axis wind turbine. In order to enhance the output power over the rated WS, the blade pitch angle (BPA) is controlled and adjusted in WT. This paper proposes and compares three different controllers of BPA for a 500-kw WT. A PID controller (PIDC), a fuzzy logic controller (FLC) based on Mamdani and Sugeno fuzzy inference systems (FIS), and a hybrid fuzzy-PID controller (HFPIDC) have been applied and compared. Furthermore, Genetic Algorithm (GA) and Particle swarm optimization (PSO) have been applied and compared in order to identify the

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Publication Date
Mon Jun 01 2015
Journal Name
Journal Of Engineering
Artificial Neural Networks Modeling of Total Dissolved Solid in the Selected Locations on Tigris River, Iraq
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The study aims to predict Total Dissolved Solids (TDS) as a water quality indicator parameter at spatial and temporal distribution of the Tigris River, Iraq by using Artificial Neural Network (ANN) model. This study was conducted on this river between Mosul and Amarah in Iraq on five positions stretching along the river for the period from 2001to 2011. In the ANNs model calibration, a computer program of multiple linear regressions is used to obtain a set of coefficient for a linear model. The input parameters of the ANNs model were the discharge of the Tigris River, the year, the month and the distance of the sampling stations from upstream of the river. The sensitivity analysis indicated that the distance and discharge

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Publication Date
Wed Jan 01 2025
Journal Name
Lecture Notes In Networks And Systems
Automated Detection of Dubas Bug Infestation in Palm Trees Using Deep Learning with Residual Neural Networks
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Automated detection of Dubas palm infestation by image processing techniques has practical significance as it can improve agricultural efficiency, increase crop yield and quality, protect the environment, and provide data-driven insights. It also reduces the human effort required for pest control and enhances sustainability. In this study, we aimed to automate the detection of Dubas bug infestation in palm trees using deep learning with transfer learning residual neural networks. Based on four models: InceptionResNetV2, ResNet18, ResNet50, and ResNet101, the data used in this study were obtained by drone photography, many images were taken, and then the infected area was extracted. Using two types of data, 185 infected images and 185 health

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Publication Date
Wed Dec 01 2010
Journal Name
Iraqi Journal Of Physics
Current–voltage and capacitance-voltage characteristics of Se/Si heterojunction prepared by DC planar magnetron sputtering technique
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In this work, the effect of annealing temperature on the electrical properties are studied of p-Se/ n-Si solar cell, which p-Se are deposit by DC planar magnetron sputtering technique on crystal silicon. The chamber was pumped down to 2×10−5 mbar before admitting the gas in. The gas was Ar. The sputtering pressure varied within the range of 4x10-1 - 8x10-2mbar by adjusting the pumping speed through the opening control of throttle valve. The electrical properties are included the C-V and I-V measurements. From C-V measurements, the Vbi are calculated while from I-V measurements, the efficiency of solar cell is calculated.

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Publication Date
Fri Jan 11 2019
Journal Name
Iraqi Journal Of Physics
Proton momentum distributions and elastic electron scattering form factors for some Ge isotopes
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The proton momentum distributions (PMD) and the elastic
electron scattering form factors F(q) of the ground state for some
even mass nuclei in the 2p-1f shell for 70Ge, 72Ge, 74Ge and 76Ge are
calculated by using the Coherent Density Fluctuation Model (CDFM)
and expressed in terms of the fluctuation function (weight function)
|F(x)|2. The fluctuation function has been related to the charge
density distribution (CDD) of the nuclei and determined from the
theory and experiment. The property of the long-tail behavior at high
momentum region of the proton momentum distribution has been
obtained by both the theoretical and experimental fluctuation
functions. The calculated form factors F (q) of all nuclei under s

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