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Fault Location of Doukan-Erbil 132kv Double Transmission Lines Using Artificial Neural Network ANN
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Transmission lines are generally subjected to faults, so it is advantageous to determine these faults as quickly as possible. This study uses an Artificial Neural Network technique to locate a fault as soon as it happens on the Doukan-Erbil of 132kv double Transmission lines network. CYME 7.1-Programming/Simulink utilized simulation to model the suggested network. A multilayer perceptron feed-forward artificial neural network with a back propagation learning algorithm is used for the intelligence locator's training, testing, assessment, and validation. Voltages and currents were applied as inputs during the neural network's training. The pre-fault and post-fault values determined the scaled values. The neural network's performance was evaluated, and tests were run. Line-to-ground faults were examined. The study demonstrates how effective, rapid, and precise this method is at locating faults. The neural network's performance was examined, and tests were run on it. The overall performance of the mean square error in the trained network execution was 0.11792 at 35 epochs. The correlation coefficient at the entire target was 0.99987 percent of an error on the Doukan-Erbil double transmission lines.

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Publication Date
Sun Mar 31 2013
Journal Name
Inventi Impact: Artificial Intelligence
SIMULATION OF IDENTIFICATION AND CONTROL OF SCARA ROBOT USING MODIFIED RECURRENT NEURAL NETWORKS
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This paper presents a modified training method for Recurrent Neural Networks. This method depends on the Non linear Auto Regressive (NARX) model with Modified Wavelet Function as activation function (MSLOG) in the hidden layer. The modified model is known as Modified Recurrent Neural (MRN). It is used for identification Forward dynamics of four Degrees of Freedom (4-DOF) Selective Compliance Assembly Robot Arm (SCARA) manipulator robot. This model is also used in the design of Direct Inverse Control (DIC). This method is compared with Recurrent Neural Networks that used Sigmoid activation function (RS) in the hidden layer and Recurrent Neural Networks with Wavelet activation function (RW). Simulation results shows that the MRN model is bett

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Publication Date
Mon Aug 27 2018
Journal Name
Al-khwarizmi Engineering Journal
Efficiency Enhancement of a Dual-axis Solar PV Panel Tracker Using Water-Flow Double Glazing Technique
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The fall angle of sun rays on the surface of a photovoltaic PV panel and its temperature is negatively affecting the panel electrical energy produced and efficiency. The fall angle problem was commonly solved by using a dual-axis solar tracker that continually maintains the panel orthogonally positioning to the sun rays all day long. This leads to maximum absorption for solar radiation necessary to produce maximum amount of energy and maintain high level of electrical efficiency. To solve the PV panel temperature problem, a Water-Flow Double Glazing WFDG technique has been introduced as a new cooling tool to reduce the panel temperature. In this paper, an integration design of the water glazing system with a dual-axis tracker has been ac

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Publication Date
Fri May 03 2024
Journal Name
Journal Of Optics
Transmission Of 10 Gb/s For Underwater Optical Wireless Communication System
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Publication Date
Tue Jan 01 2019
Journal Name
Cogent Engineering
IEC 60909 and ANSI standards comparison with ASCC based fault calculations of Iraqi power system
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Publication Date
Thu Mar 01 2018
Journal Name
Journal Of Engineering
Analysis of Double Skin Composite Slabs
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This paper deals with finite element modeling of the ultimate load behavior of double skin composite (DSC) slabs. In a DSC slab, shear connectors in the form of nut bolt technique studs are used to transfer shear between the outer skin made of steel plates and the concrete core. The current study is based on finite element analysis using ANSYS Version 11 APDL release computer program. Experimental programmes were carried out by the others, two simply supported DSC beams were tested until failure under a concentrated load applied at the center. These test specimens were analyzed by the finite element method and the analyses have shown that these slabs displayed a high degree of flexural characteristics, ultimate strength,

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Publication Date
Sun Mar 01 2015
Journal Name
Iraqi Journal Of Science
Spectroscopic Study of the Forbidden Lines [OIII] and [SII] of Crab Nebula Supernova Remnant
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As a star explode as a supernova its ejecta will directly interact with relativelylow density interstellar medium with high shock wave velocity, and due to thisinteraction many of forbidden emission lines will give a raise from both theexcitation and ionization of the atom in the region. So, the study of these emissionlines can reveal many physical properties of the region, in this case the remnant ofthe supernova, such as temperature, density, composition, and many other importantphysical processes. In this paper the optical spectrum of the young galacticsupernova remnant which is the Crab Nebula has used, in order to calculate it’selectron temperature (Te) and electron density (ne) by using the [OIII] and [SII]forbidden lines. From the

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Publication Date
Tue Nov 09 2021
Journal Name
Abu Dhabi International Petroleum Exhibition & Conference
Numerical Simulation of Gas Lift Optimization Using Artificial Intelligence for a Middle Eastern Oil Field
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Abstract<p>Artificial lift techniques are a highly effective solution to aid the deterioration of the production especially for mature oil fields, gas lift is one of the oldest and most applied artificial lift methods especially for large oil fields, the gas that is required for injection is quite scarce and expensive resource, optimally allocating the injection rate in each well is a high importance task and not easily applicable. Conventional methods faced some major problems in solving this problem in a network with large number of wells, multi-constrains, multi-objectives, and limited amount of gas. This paper focuses on utilizing the Genetic Algorithm (GA) as a gas lift optimization algorit</p> ... Show More
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Publication Date
Sun Dec 31 2023
Journal Name
Sumer Journal For Pure Science
COVID-19Disease Diagnosis using Artificial Intelligence based on Gene Expression: A Review
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Publication Date
Sat Jan 01 2022
Journal Name
Journal Of Pharmaceutical Negative Results
Environmental effects on intestinal parasitic disease transmission in Mosul governorate
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This study, which was conducted in the city of Mosul, through collected 1200 samples from the stool of patients with diarrhea attending hospitals and private clinics for the period from the beginning of January 2019 to the end of December 2019, those whose ages ranged from less than a year-60 year, and for both sexes and by reality 700 samples stool for males and 500 samples stool for females. Samples were collected in clean, sterile, and sealed 40ml plastic bottles. Patient information is noted, name of the parasite, history, sex, age, address. The result showed that climate and temperature have a significant effect on increase the incidence of intestinal parasites through the direct effect on the increase in infection rate. This effect wa

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Publication Date
Thu Aug 31 2017
Journal Name
Journal Of Engineering
Study and Analysis of Concentric Shell and Double Tube Heat Exchanger Using - Al 2 O 3 Nanofluid
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    Heat exchanger is an important device in the industry for cooling or heating process. To increase the efficiency of heat exchanger, nanofluids are used to enhance the convective heat . transfer relative to the base fluid. - Al2O3/water nanofluid is used as cold stream in the shell and double concentric tube heat exchanger counter current to the hot stream basis oil. These nanoparticles were of particle size of 40 nm and it was mixed with a base fluid (water) at volume
concentrations of 0.002% and 0.004%. The results showed that each of Nusselt number and overall heat transfer coefficient increased as nanofluid concentrations increased. The pressure drop of nanofluid increased slightly than the base fluid because

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