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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
Sun Jun 06 2010
Journal Name
Baghdad Science Journal
Comparison between the efficiency of serological tests for Identification of Brucellosis
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Five serological methods for detection of Brucella were compaired in this study, Four of the methods are commonely used in the detections:- 1-Rose-Bengal: as primary screening test which depends on detecting antibodies in the blood serum. 2-IFAT: which detects IgG and IgM antibodies in the serum. 3-ELISA test: which detects IgG antibodies in the serum. 4-2ME test: which detects IgG antibodies The fifth methods. It was developed by a reasercher in one of the health centers in Baghdad. It was given the name of spot Immune Assay (SIA). Results declares that among (100) samples of patients blood, 76, 49, 49, 37, and 28. samples were positive to Rose Bengal, ELISA, SIA, 2ME and IFAT tests, respectively. When efficiency, sensitivity and specific

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Publication Date
Sat Aug 01 2020
Journal Name
Journal Of Engineering Science And Technology (jestec)
Influence of A River Water Quality on The Efficiency of Water Treatment Using Artificial Neural Network
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Tigris River is the lifeline that supplies a great part of Iraq with water from north to south. Throughout its entire length, the river is battered by various types of pollutants such as wastewater effluents from municipal, industrial, agricultural activities, and others. Hence, the water quality assessment of the Tigris River is crucial in ensuring that appropriate and adequate measures are taken to save the river from as much pollution as possible. In this study, six water treatment plants (WTPs) situated on the two-banks of the Tigris within Baghdad City were Al Karkh; Sharq Dijla; Al Wathba; Al Karama; Al Doura, and Al Wahda from northern Baghdad to its south, that selected to determine the removal efficiency of turbidity and

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Publication Date
Tue Dec 13 2022
Journal Name
Lecture Notes In Networks And Systems
Design and FPGA Implementation of Matrix Multiplier Using DEMUX-RCA-Based Vedic Multiplier
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Publication Date
Fri Mar 01 2019
Journal Name
Al-khwarizmi Engineering Journal
A Digital-Based Optimal AVR Design of Synchronous Generator Exciter Using LQR Technique
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In this paper a new structure for the AVR of the power system exciter is proposed and designed using digital-based LQR. With two weighting matrices R and Q,  this method produces an optimal regulator that is used to generate the feedback control law. These matrices are called state and control weighting matrices and are used to balance between the relative importance of the input and the states in the cost function that is being optimized. A sample power system composed of single machine connected to an infinite- bus bar (SMIB) with both a conventional and a proposed Digital AVR (DAVR) is simulated. Evaluation results show that the DAVR damps well the oscillations of the terminal voltage and presents a faster respo

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Publication Date
Wed Nov 01 2017
Journal Name
Journal Of Computational And Theoretical Nanoscience
Solution for Multi-Objective Optimisation Master Production Scheduling Problems Based on Swarm Intelligence Algorithms
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The emphasis of Master Production Scheduling (MPS) or tactic planning is on time and spatial disintegration of the cumulative planning targets and forecasts, along with the provision and forecast of the required resources. This procedure eventually becomes considerably difficult and slow as the number of resources, products and periods considered increases. A number of studies have been carried out to understand these impediments and formulate algorithms to optimise the production planning problem, or more specifically the master production scheduling (MPS) problem. These algorithms include an Evolutionary Algorithm called Genetic Algorithm, a Swarm Intelligence methodology called Gravitational Search Algorithm (GSA), Bat Algorithm (BAT), T

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Publication Date
Sun Mar 01 2020
Journal Name
Baghdad Science Journal
Dynamic Response of a Nonlinear Fabry-Perot Etalon for Various Medium Response Times
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     In this work, the switching nonlinear dynamics of a Fabry-Perot etalon are studied. The method used to complete the solution of the differential equations for the nonlinear medium. The Debye relaxation equations solved numerically to predict the behavior of the cavity for modulated input power. The response of the cavity filled with materials of different response time is depicted. For a material with a response time equal to = 50 ns, the cavity switches after about (100 ns). Notice that there is always a finite time delay before the cavity switches. The switch up time is much longer than the cavity build-up time of the corresponding linear cavity which was found to be of the order of a few round-trip ti

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Publication Date
Thu Feb 28 2019
Journal Name
Journal Of Engineering
Frequency Domain Analysis for Geometric Nonlinear Seismic Response of Tall Reinforced Concrete Buildings
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This paper aims to study the second-order geometric nonlinearity effects of P-Delta on the dynamic response of tall reinforced concrete buildings due to a wide range of earthquake ground motion forces, including minor earthquake up to moderate and strong earthquakes. The frequency domain dynamic analysis procedure was used for response assessment. Reinforced concrete building models with different heights up to 50 stories were analyzed. The finite element software ETABS (version 16.0.3) was used to analyze reinforced concrete building models.

The study reveals that the percentage increase in buildings' sway and drift due to P-Delta effects are nearly constant for specific building height irrespective of the seism

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Publication Date
Thu Oct 01 2020
Journal Name
Alexandria Engineering Journal
The operational matrix of Legendre polynomials for solving nonlinear thin film flow problems
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Publication Date
Thu Oct 01 2020
Journal Name
Alexandria Engineering Journal
The operational matrix of Legendre polynomials for solving nonlinear thin film flow problems
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Publication Date
Mon Jun 19 2023
Journal Name
Journal Of Engineering
Data Classification using Quantum Neural Network
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In this paper, integrated quantum neural network (QNN), which is a class of feedforward

neural networks (FFNN’s), is performed through emerging quantum computing (QC) with artificial neural network(ANN) classifier. It is used in data classification technique, and here iris flower data is used as a classification signals. For this purpose independent component analysis (ICA) is used as a feature extraction technique after normalization of these signals, the architecture of (QNN’s) has inherently built in fuzzy, hidden units of these networks (QNN’s) to develop quantized representations of sample information provided by the training data set in various graded levels of certainty. Experimental results presented here show that

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