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Control on a 2-D Wing Flutter Using an Adaptive Nonlinear Neural Controller
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An adaptive nonlinear neural controller to reduce the nonlinear flutter in 2-D wing is proposed in the paper. The nonlinearities in the system come from the quasi steady aerodynamic model and torsional spring in pitch direction. Time domain simulations are used to examine the dynamic aero elastic instabilities of the system (e.g. the onset of flutter and limit cycle oscillation, LCO). The structure of the controller consists of two models :the modified Elman neural network (MENN) and the feed forward multi-layer Perceptron (MLP). The MENN model is trained with off-line and on-line stages to guarantee that the outputs of the model accurately represent the plunge and pitch motion of the wing and this neural model acts as the identifier. The feed forward neural controller is trained off-line and adaptive weights are implemented on-line to find the flap angles, which controls the plunge and pitch motion of the wing. The general back propagation algorithm is used to learn the feed forward neural controller and the neural identifier. The simulation results show the effectiveness of the proposed control algorithm; this is demonstrated by the minimized tracking error to zero approximation with very acceptable settling time even with the existence of bounded external disturbances.

 

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Publication Date
Wed Dec 13 2017
Journal Name
Al-khwarizmi Engineering Journal
Performance Comparison of Different Advanced Control Schemes for Glucose Level Control under Disturbing Meal
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Abstract

In this work, diabetic glucose concentration level control under disturbing meal has been controlled using two set of advanced controllers. The first set is sliding mode controllers (classical and integral) and the second set is represented by optimal LQR controllers (classical and Min-, ax). Due to their characteristic features of disturbance rejection, both integral sliding mode controller and LQR Minmax controller are dedicated here for comparison. The Bergman minimal mathematical model was used to represent the dynamic behavior of a diabetic patient’s blood glucose concentration to the insulin injection. Simulations based on Matlab/Simulink, were performed to verify the performance of each controll

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Publication Date
Mon Nov 30 2020
Journal Name
Journal Of Economics And Administrative Sciences
Evaluating Quality of Control Policies and Procedures for Banking Transactions Using the Non-application Gap Model to Enhance Financial Reporting Requirements Applied Study in an Iraqi Private Bank
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The research aims to enhance the level of evaluation of the performance of banking transactions control policies and procedures. The research is based on the following hypothesis: efficient transactions control policies and procedures contribute enhancing financial reporting, by assessing non-application gap of those policies and procedures in a manner that helps to prevent, discover, and correct material misstatementsThe researchers designed an examination list that includes the control policies and procedures related to the transactions, as a guide to the bank audit program prepared by the Federal Financial Supervision Bureau. The research methodology is

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Publication Date
Fri Feb 10 2023
Journal Name
Journal Of Applied Mathematics
The Dynamics of a Delayed Ecoepidemiological Model with Nonlinear Incidence Rate
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In this paper, the general framework for calculating the stability of equilibria, Hopf bifurcation of a delayed prey-predator system with an SI type of disease in the prey population, is investigated. The impact of the incubation period delay on disease transmission utilizing a nonlinear incidence rate was taken into account. For the purpose of explaining the predation process, a modified Holling type II functional response was used. First, the existence, uniform boundedness, and positivity of the solutions of the considered model system, along with the behavior of equilibria and the existence of Hopf bifurcation, are studied. The critical values of the delay parameter for which stability switches and the nature of the Hopf bifurcat

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Publication Date
Tue Dec 01 2009
Journal Name
Journal Of Economics And Administrative Sciences
Using Artificial Neural Network Models For Forecasting & Comparison
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The Artificial Neural Network methodology is a very important & new subjects that build's the models for Analyzing, Data Evaluation, Forecasting & Controlling without depending on an old model or classic statistic method that describe the behavior of statistic phenomenon, the methodology works by simulating the data to reach a robust optimum model that represent the statistic phenomenon & we can use the model in any time & states, we used the Box-Jenkins (ARMAX) approach for comparing, in this paper depends on the received power to build a robust model for forecasting, analyzing & controlling in the sod power, the received power come from

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Publication Date
Sat Feb 09 2019
Journal Name
Journal Of The College Of Education For Women
Key Exchange Management by using Neural Network Synchronization
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The paper presents a neural synchronization into intensive study in order to address challenges preventing from adopting it as an alternative key exchange algorithm. The results obtained from the implementation of neural synchronization with this proposed system address two challenges: namely the verification of establishing the synchronization between the two neural networks, and the public initiation of the input vector for each party. Solutions are presented and mathematical model is developed and presented, and as this proposed system focuses on stream cipher; a system of LFSRs (linear feedback shift registers) has been used with a balanced memory to generate the key. The initializations of these LFSRs are neural weights after achiev

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Publication Date
Wed Feb 01 2023
Journal Name
Trends Technological And Science ,engineering
Automated Sorting for Tomatoes using Artificial Neural Network
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A .technology analysis image using crops agricultural of grading and sorting the test to conducted was experiment The device coupling the of sensor a with camera a and 75 * 75 * 50 dimensions with shape cube studio made-factory locally the study to studio the in taken were photos and ,)blue-green - red (lighting triple with equipped was studio The .used were neural artificial and technology processing image using maturity and quality ,damage of fruits the of characteristics external value the quality 0.92062, of was value regression the damage predict to used was network neural artificial The .network the using scheme regression a of means by 0.98654 of was regression the of maturity and 0.97981 of was regression the of .algorithm Marr

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Publication Date
Sun Mar 03 2019
Journal Name
Iraqi Journal Of Physics
Experimental observation of the far field diffraction patterns of functionalization single and multi-walled carbon nanotubes using nonlinear diffraction technique
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Nonlinear diffraction pattern can be induced by focusing CW
laser into a thin quartzes cuvette containing nanofluid. The number
of revealed pattern rings indicates to the nonlinear behavior of fluid.
Here, the nonlinear refractive index of each of functionalized single
wall carbon nanotube (F-SWCNTs) suspention and multi wall carbon
nanotube (F-MWCNTs) suspention have been investigated
experimentally .Each of CNTs suspention was at volume fraction of
13×10−5 and 6×10−5. Moreover the laser source at wavelength of
473 nm was used. The results show that SWCNTs suspention
possesses higher nonlinearty than other at the same volume fraction

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Publication Date
Wed Sep 01 2021
Journal Name
Journal Of Petroleum Science And Engineering
Factors affecting gel strength design for conformance control: An integrated investigation
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Publication Date
Sun May 01 2022
Journal Name
Journal Of Engineering
Estimating Pitting Corrosion Depth and Density on Carbon Steel (C-4130) using Artificial Neural Networks
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The purpose of this research is to investigate the impact of corrosive environment (corrosive ferric chloride of 1, 2, 5, 6% wt. at room temperature), immersion period of (48, 72, 96, 120, 144 hours), and surface roughness on pitting corrosion characteristics and use the data to build an artificial neural network and test its ability to predict the depth and intensity of pitting corrosion in a variety of conditions. Pit density and depth were calculated using a pitting corrosion test on carbon steel (C-4130). Pitting corrosion experimental tests were used to develop artificial neural network (ANN) models for predicting pitting corrosion characteristics. It was found that artificial neural network models were shown to be

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Publication Date
Sun Feb 22 2026
Journal Name
Journal Of Al-farahidi's Arts
Artificial Intelligence Tools in Literary Text Analysis: An Applied Study Using Voyant Tool: The Poem “I have now a Rifle” by Nizar Qabbani as a Model
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In recent years, literary studies have witnessed a remarkable shift towards employing digital technologies, particularly artificial intelligence tools, in analyzing literary texts and exploring their linguistic and semantic structures. This trend has provided researchers with new possibilities for understanding texts in quantitative and qualitative ways that transcend traditional methods based solely on critical reading. The current research aims to introduce professors and students of Arabic to artificial intelligence tools that contribute to the analysis of literary texts, focusing on exploring their mechanisms for studying style, meaning, structure, and emotion. It also seeks to highlight the most prominent challenges facing researchers

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