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Design of New Hybrid Neural Structure for Modeling and Controlling Nonlinear Systems
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This paper proposes a new structure of the hybrid 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. Weight parameters of the hybrid neural structure with its serial-parallel configuration are adapted by using the Back propagation learning algorithm. The ability of the proposed hybrid neural structure for nonlinear system has achieved a fast learning with minimum number of epoch, minimum number of neurons in the hybrid network, high accuracy in the output without oscillation response as well as useful model for a one step ahead prediction controller for the nonlinear CSTR system that is used in the MATLAB simulation.

 

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Publication Date
Thu Aug 30 2018
Journal Name
Iraqi Journal Of Science
Symmetrical Fibonacci and Lucas Wave Solutions for Some Nonlinear Equations in Higher Dimensions
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We consider some nonlinear partial differential equations in higher dimensions, the negative order of the Calogero-Bogoyavelnskii-Schiff (nCBS) equationin (2+1) dimensions, the combined of the Calogero-Bogoyavelnskii-Schiff equation and the negative order of the Calogero-Bogoyavelnskii-Schiff equation (CBS-nCBS) in (2+1) dimensions, and two models of the negative order Korteweg de Vries (nKdV) equations in (3+1) dimensions. We show that these equations can be reduced to the  same class of ordinary differential equations via wave reduction variable. Solutions in terms of symmetrical Fibonacci and Lucas functions are presented by implementation of the modified Kudryashov method.

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Publication Date
Tue Feb 28 2023
Journal Name
Iraqi Journal Of Science
Solvability for Optimal Classical Continuous Control Problem Controlling by Quaternary Hyperbolic Boundary Value Problem
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    This work is concerned with studying the solvability for optimal classical continuous control quaternary vector problem that controls by quaternary linear hyperbolic boundary value problem. The existence of the unique quaternary state vector solution for the quaternary linear hyperbolic boundary value problem  is studied and demonstrated by employing the method of Galerkin, where the classical continuous control quaternary vector  is Known. Also, the existence theorem of an optimal classical continuous control quaternary vector related to the quaternary linear hyperbolic boundary value problem is demonstrated. The existence of a unique solution to the adjoint quaternary linear hyperbolic boundary value problem a

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Publication Date
Sat Jan 30 2021
Journal Name
Iraqi Journal Of Science
Signal Soft Sets for Atoms Modeling and Signal Soft Topology
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In this paper we define a signal soft set as a mathematical tool to represent and study atoms, anti-atoms, electrons, anti-electrons, protons, and anti-protons, and generate a signal soft topology, with an example of signal soft topology on H2O.

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Publication Date
Mon Jan 15 2018
Journal Name
Scientific Reports
Tuning charge carrier transport and optical birefringence in liquid-crystalline thin films: A new design space for organic light-emitting diodes
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Abstract<p>Liquid-crystalline organic semiconductors exhibit unique properties that make them highly interesting for organic optoelectronic applications. Their optical and electrical anisotropies and the possibility to control the alignment of the liquid-crystalline semiconductor allow not only to optimize charge carrier transport, but to tune the optical property of organic thin-film devices as well. In this study, the molecular orientation in a liquid-crystalline semiconductor film is tuned by a novel blading process as well as by different annealing protocols. The altered alignment is verified by cross-polarized optical microscopy and spectroscopic ellipsometry. It is shown that a change in alignment of the </p> ... Show More
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Publication Date
Thu Aug 30 2018
Journal Name
Iraqi Journal Of Science
Construct a New System as a Combining Function for the LFSR in the Stream Cipher Systems Using Multiplicative Cyclic Group
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In this paper, we construct a new mathematical system as Multiplicative Cyclic Group (MCG), called a New Digital Algebraic Generator (NDAG) Unit, which would generate digital sequences with good statistical properties. This new Unit can be considered as a new basic unit of stream ciphers.

A (NDAG) system can be constructed from collection of (NDAG) units using a Boolean function as a combining function of the system. This system could be used in cryptography as like as Linear Feedback Shift Register (LFSR) unit. This unit is basic component of  a stream cipher system.

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Publication Date
Sun Sep 05 2010
Journal Name
Baghdad Science Journal
Volterra Runge- Kutta Methods for Solving Nonlinear Volterra Integral Equations
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In this paper Volterra Runge-Kutta methods which include: method of order two and four will be applied to general nonlinear Volterra integral equations of the second kind. Moreover we study the convergent of the algorithms of Volterra Runge-Kutta methods. Finally, programs for each method are written in MATLAB language and a comparison between the two types has been made depending on the least square errors.

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Publication Date
Sat Jun 27 2020
Journal Name
Iraqi Journal Of Science
The Performance Differences between Using Recurrent Neural Networks and Feedforward Neural Network in Sentiment Analysis Problem
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 With the spread use of internet, especially the web of social media, an unusual quantity of information is found that includes a number of study fields such as psychology, entertainment, sociology, business, news, politics, and other cultural fields of nations. Data mining methodologies that deal with social media allows producing enjoyable scene on the human behaviour and interaction. This paper demonstrates the application and precision of sentiment analysis using traditional feedforward and two of recurrent neural networks (gated recurrent unit (GRU) and long short term memory (LSTM)) to find the differences between them. In order to test the system’s performance, a set of tests is applied on two public datasets. The firs

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Publication Date
Wed Feb 20 2019
Journal Name
Political Sciences Journal
Article Japan's social structure and useful Implications for Iraq
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The development of Japanese society passed through long historical stages and as a result of the bitter experience of Japan in the Second World War and its exhaustion, it was able to build a modern modern state after 1945. Japan is a country of culture, civilization, science and technology, a country that appreciates the value of solidarity work. And the role of active civil society. This is what makes us in Iraq stand and draw their experience in the advancement and development, especially that they also passed bitter political stages, Iraq today passes through the most historical periods of forestry through its historical heritage in terms of the existence of complex social problems, the US occupation of Iraq in 2003 highlighte

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Publication Date
Fri Jan 01 2016
Journal Name
Computational Intelligence And Neuroscience
A New Artificial Neural Network Approach in Solving Inverse Kinematics of Robotic Arm (Denso VP6242)
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This paper presents a novel inverse kinematics solution for robotic arm based on artificial neural network (ANN) architecture. The motion of robotic arm is controlled by the kinematics of ANN. A new artificial neural network approach for inverse kinematics is proposed. The novelty of the proposed ANN is the inclusion of the feedback of current joint angles configuration of robotic arm as well as the desired position and orientation in the input pattern of neural network, while the traditional ANN has only the desired position and orientation of the end effector in the input pattern of neural network. In this paper, a six DOF Denso robotic arm with a gripper is controlled by ANN. The comprehensive experimental results proved the appl

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Publication Date
Mon Aug 01 2022
Journal Name
Baghdad Science Journal
Performance Assessment of Solar-Transformer-Consumption System Using Neural Network Approach
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Solar energy is one of the immeasurable renewable energy in power generation for a green, clean and healthier environment. The silicon-layer solar panels absorb sun energy and converts it into electricity by off-grid inverter. Electricity is transferred either from this inverter or from transformer, consumed by consumption unit(s) available for residential or economic purposes. The artificial neural network is the foundation of artificial intelligence and solves many complex problems which are difficult by statistical methods or by humans. In view of this, the purpose of this work is to assess the performance of the Solar - Transformer - Consumption (STC) system. The system may be in complete breakdown situation due to failure of both so

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