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Design of New Hybrid Neural Controller for Nonlinear CSTR System based on Identification
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This paper proposes improving the structure of the neural controller based on the identification model for nonlinear systems. The goal of this work is to employ the structure of the Modified Elman Neural Network (MENN) model into the NARMA-L2 structure instead of Multi-Layer Perceptron (MLP) model in order to construct a new hybrid neural structure that can be used as an identifier model and a nonlinear controller for the SISO linear or nonlinear systems. Two learning algorithms are used to adjust the parameters weight of the hybrid neural structure with its serial-parallel configuration; the first one is supervised learning algorithm based Back Propagation Algorithm (BPA) and the second one is an intelligent algorithm namely Particle Swarm Optimization (PSO) algorithm. The numerical simulation results show that the hybrid NARMA-L2 controller with PSO algorithm is more accurate than BPA in terms of achieving fast learning and adjusting the parameters model with minimum number of iterations, minimum number of neurons in the hybrid network and the smooth output one step ahead prediction controller response for the nonlinear CSTR system without oscillation.

 

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Publication Date
Mon Aug 01 2016
Journal Name
Journal Of Economics And Administrative Sciences
Job involvement for workers and its influence in Crystallize organizational Identification (An analytical research of the opinions of a sample of workers in the Middle East, the Iraqi Investment Bank)
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Abstract:

     The current research is aimed at analyzing the impact of the dimensions of Job involvement of all of (the enthusiasm, the Devotion, Assimilation ) in the Crystallize organizational Identification across the dimensions of (organizational loyalty, membership, similarities) and was named the Middle East, the Iraqi Investment Bank room to look as the research community of staff adopted in the bank, to be applied to a Random sample of (100) employees working in the said bank, and developed for the purposes of data collection, a questionnaire form included three axes covered (32) paragraph of the measure, which is included adopted Liekrt Quintet for the

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Publication Date
Mon Sep 13 2021
Journal Name
Al-khwarizmi Engineering Journal
Optimization of Cutting Parameters for Milling Process of (4032) Al-Alloy using Taguchi-Based Grey Relational Analysis
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The objective of this work is to study the influence of end milling cutting process parameters, tool material and geometry on multi-response outputs for 4032 Al-alloy. This can be done by proposing an approach that combines Taguchi method with grey relational analysis. Three cutting parameters have been selected (spindle speed, feed rate and cut depth) with three levels for each parameter. Three tools with different materials and geometry have been also used to design the experimental tests and runs based on matrix L9. The end milling process with several output characteristics is solved using a grey relational analysis. The results of analysis of variance (ANOVA) showed that the major influencing parameters on multi-objective response w

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Publication Date
Mon Dec 20 2021
Journal Name
Baghdad Science Journal
Performance Analysis of Propagation in VHF Military Tactical Communication System
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The main challenge of military tactical communication systems is the accessibility of relevant information on the particular operating environment required for the determination of the waveform's ideal use. The existing propagation model focuses mainly on broadcasting and commercial wireless communication with a highs transceiver antenna that is not suitable for numerous military tactical communication systems. This paper presents a study of the path loss model related to radio propagation profile within the suburban in Kuala Lumpur. The experimental path loss modeling for VHF propagation was collected from various suburban settings for the 30-88 MHz frequency range. This experiment was highly affected by ecological factors and existing

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Publication Date
Sun Dec 15 2019
Journal Name
Al-academy
The Effect of The Illustration Program on Fashion Design Inspired by Historical Costumes: تهاني ناصر العجاجي -هدى عبد العزيز المقرن
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This research aims to identify the role and impact of illustrations in contemporary fashion design inspired by historical costumes. Historical fashion aesthetics are adapted to design drawings. The experimental method was followed and a sample of 31 students in the department of fashion and textile design, third level were selected. Each student carried out two original historical and contemporary design. The models were executed two times: one with the usage of the program and the other without program help. The tools that were used are the program, the scale, the pre-skill test, and the post-skill test. One of the most relevant results of the research is the possibility of using historical costumes to highlight creativity and innovatio

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Publication Date
Fri May 01 2015
Journal Name
Journal Of Engineering
A Real-Coded Genetic Algorithm with System Reduction and Restoration for Rapid and Reliable Power Flow Solution of Power Systems
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The paper presents a highly accurate power flow solution, reducing the possibility of ending at local minima, by using Real-Coded Genetic Algorithm (RCGA) with system reduction and restoration. The proposed method (RCGA) is modified to reduce the total computing time by reducing the system in size to that of the generator buses, which, for any realistic system, will be smaller in number, and the load buses are eliminated. Then solving the power flow problem for the generator buses only by real-coded GA to calculate the voltage phase angles, whereas the voltage magnitudes are specified resulted in reduced computation time for the solution. Then the system is restored by calculating the voltages of the load buses in terms

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Publication Date
Mon Mar 07 2022
Journal Name
Journal Of Inorganic And Organometallic Polymers And Materials
Mechanical Characteristics and Thermal Stability of Hybrid Epoxy and Acrylic Polymer Coating/Nanoclay of Various Thicknesses
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Publication Date
Thu Aug 01 2019
Journal Name
The Journal Of Solid Waste Technology And Management
Recycling of Waste Compact Discs in Concrete Mix: Lab Investigations and Artificial Neural Networks Modeling
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This study aimed to investigate the incorporation of recycled waste compact discs (WCDs) powder in concrete mixes to replace the fine aggregate by 5%, 10%, 15% and 20%. Compared to the reference concrete mix, results revealed that using WCDs powder in concrete mixes improved the workability and the dry density. The results demonstrated that the compressive, flexural, and split tensile strengths values for the WCDs-modified concrete mixes showed tendency to increase above the reference mix. However, at 28 days curing age, the strengths values for WCDs-modified concrete mixes were comparable to those for the reference mix. The leaching test revealed that none of the WCDs constituents was detected in the leachant after 180 days. The

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Publication Date
Tue May 01 2018
Journal Name
Journal Of Engineering
Prediction of Municipal Solid Waste Generation Models Using Artificial Neural Network in Baghdad city, Iraq
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The importance of Baghdad city as the capital of Iraq and the center of the attention of delegations because of its long history is essential to preserve its environment. This is achieved through the integrated management of municipal solid waste since this is only possible by knowing the quantities produced by the population on a daily basis. This study focused to predicate the amount of municipal solid waste generated in Karkh and Rusafa separately, in addition to the quantity produced in Baghdad, using IBM SPSS 23 software. Results that showed the average generation rates of domestic solid waste in Rusafa side was higher than that of Al-Karkh side because Rusafa side has higher population density than Al-Karkh side. T

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Publication Date
Thu Sep 01 2022
Journal Name
Iraqi Journal Of Physics
Development and Assessment of Feed Forward Back Propagation Neural Network Models to Predict Sunshine Duration
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         The duration of sunshine is one of the important indicators and one of the variables for measuring the amount of solar radiation collected in a particular area. Duration of solar brightness has been used to study atmospheric energy balance, sustainable development, ecosystem evolution and climate change. Predicting the average values of sunshine duration (SD) for Duhok city, Iraq on a daily basis using the approach of artificial neural network (ANN) is the focus of this paper. Many different ANN models with different input variables were used in the prediction processes. The daily average of the month, average temperature, maximum temperature, minimum temperature, relative humidity, wind direction, cloud level and atmosp

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Publication Date
Thu Oct 01 2020
Journal Name
Journal Of Engineering Science And Technology
Water quality assessment and sodium adsorption ratio prediction of Tigris River using artificial neural network
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