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Model Reference Adaptive Control based on a Self-Recurrent Wavelet Neural Network Utilizing Micro Artificial Immune Systems
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Abstract 

This paper presents an intelligent model reference adaptive control (MRAC) utilizing a self-recurrent wavelet neural network (SRWNN) to control nonlinear systems. The proposed SRWNN is an improved version of a previously reported wavelet neural network (WNN). In particular, this improvement was achieved by adopting two modifications to the original WNN structure. These modifications include, firstly, the utilization of a specific initialization phase to improve the convergence to the optimal weight values, and secondly, the inclusion of self-feedback weights to the wavelons of the wavelet layer. Furthermore, an on-line training procedure was proposed to enhance the control performance of the SRWNN-based MRAC. As the training method, the recently developed modified micro artificial immune system (MMAIS) was used to optimize the parameters of the SRWNN. The effectiveness of this control approach was demonstrated by controlling several nonlinear dynamical systems. For each of these systems, several evaluation tests were conducted, including control performance tests, robustness tests, and generalization tests. From these tests, the SRWNN-based MRAC has exhibited its effectiveness regarding accurate control, disturbance rejection, and generalization ability. In addition, a comparative study was made with other related controllers, namely the original WNN, the artificial neural network (ANN), and the modified recurrent network (MRN). The results of these comparison tests indicated the superiority of the SRWNN controller over the other related controllers.

Keywords: Artificial neural network, micro artificial immune system, model reference adaptive control, self-recurrent wavelet neural network , Wavelet neural network.

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Publication Date
Thu Dec 28 2017
Journal Name
Al-khwarizmi Engineering Journal
Obstacles Avoidance for Mobile Robot Using Enhanced Artificial Potential Field
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In this paper, an enhanced artificial potential field (EAPF) planner is introduced. This planner is proposed to rapidly find online solutions for the mobile robot path planning problems, when the underlying environment contains obstacles with unknown locations and sizes. The classical artificial potential field represents both the repulsive force due to the detected obstacle and the attractive force due to the target. These forces can be considered as the primary directional indicator for the mobile robot. However, the classical artificial potential field has many drawbacks. So, we suggest two secondary forces which are called the midpoint

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Publication Date
Tue Dec 05 2023
Journal Name
Baghdad Science Journal
An improved neurogenetic model for recognition of 3D kinetic data of human extracted from the Vicon Robot system
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These days, it is crucial to discern between different types of human behavior, and artificial intelligence techniques play a big part in that.  The characteristics of the feedforward artificial neural network (FANN) algorithm and the genetic algorithm have been combined to create an important working mechanism that aids in this field. The proposed system can be used for essential tasks in life, such as analysis, automation, control, recognition, and other tasks. Crossover and mutation are the two primary mechanisms used by the genetic algorithm in the proposed system to replace the back propagation process in ANN. While the feedforward artificial neural network technique is focused on input processing, this should be based on the proce

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Publication Date
Thu Nov 17 2016
Journal Name
Plos One
Efficient and Stable Routing Algorithm Based on User Mobility and Node Density in Urban Vehicular Network
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Vehicular ad hoc networks (VANETs) are considered an emerging technology in the industrial and educational fields. This technology is essential in the deployment of the intelligent transportation system, which is targeted to improve safety and efficiency of traffic. The implementation of VANETs can be effectively executed by transmitting data among vehicles with the use of multiple hops. However, the intrinsic characteristics of VANETs, such as its dynamic network topology and intermittent connectivity, limit data delivery. One particular challenge of this network is the possibility that the contributing node may only remain in the network for a limited time. Hence, to prevent data loss from that node, the information must reach the destina

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Publication Date
Sat Feb 15 2025
Journal Name
Iraqi Journal Of Pharmaceutical Sciences
Academic Staff Perspectives on the Impact of Artificial Intelligence on Pharmaceutical Sciences Research and Writing: A Qualitative Study.
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Artificial intelligence (AI) offers significant benefits to biomedical research and academic writing. Nevertheless, using AI-powered writing aid tools has prompted worries about excessive dependence on these tools and their possible influence on writing proficiency. The current study aimed to explore the academic staff’s perspectives on the impact of AI on academic writing. This qualitative study incorporated in-person interviews with academic faculty members. The interviews were conducted in a semi-structured manner, using a predetermined interview guide consisting of open-ended questions. The interviews were done in person with the participants from May to November 2023. The data was analyzed using thematic analysis. Ten academics aged

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Publication Date
Thu Feb 07 2019
Journal Name
Iraqi Journal Of Laser
Laser Enhanced Photocatalyic Degradation of Methylene blue using Nanostructured ZnO Catalyst based on Interfacial Charge Transfer
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In this research, annealed nanostructured ZnO catalyst water putrefaction system was built using sun light and different wavelength lasers as stimulating light sources to enhance photocatalytic degradation activity of methylene blue (MB) dye as a model based on interfacial charges transfer. The structural, crystallite size, morphological, particle size, optical properties and degradation ability of annealed nanostructured ZnO were characterized by X-Ray Diffraction (XRD), Atomic Force Microscopy (AFM) and UV-VIS Spectrometer, respectively. XRD results demonstrated a pure crystalline hexagonal wurtzite with crystalline size equal to 23 nm. From AFM results, the average particle size was 79.25nm. All MB samples and MB with annealed nanostr

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Publication Date
Tue Mar 30 2021
Journal Name
Baghdad Science Journal
Delivery Route Management based on Dijkstra Algorithm
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For businesses that provide delivery services, the efficiency of the delivery process in terms of punctuality is very important. In addition to increasing customer trust, efficient route management, and selection are required to reduce vehicle fuel costs and expedite delivery. Some small and medium businesses still use conventional methods to manage delivery routes. Decisions to manage delivery schedules and routes do not use any specific methods to expedite the delivery settlement process. This process is inefficient, takes a long time, increases costs and is prone to errors. Therefore, the Dijkstra algorithm has been used to improve the delivery management process. A delivery management system was developed to help managers and drivers

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Publication Date
Wed Jan 13 2016
Journal Name
University Of Baghdad
Employ Mathematical Model and Neural Networks for Determining Rate Environmental Contamination
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Publication Date
Thu Jun 01 2023
Journal Name
Electronics
Downlink Training Sequence Design Based on Waterfilling Solution for Low-Latency FDD Massive MIMO Communications Systems
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Future generations of wireless communications systems are expected to evolve toward allowing massive ubiquitous connectivity and achieving ultra-reliable and low-latency communications (URLLC) with extremely high data rates. Massive multiple-input multiple-output (m-MIMO) is a crucial transmission technique to fulfill the demands of high data rates in the upcoming wireless systems. However, obtaining a downlink (DL) training sequence (TS) that is feasible for fast channel estimation, i.e., meeting the low-latency communications required by future generations of wireless systems, in m-MIMO with frequency-division-duplex (FDD) when users have different channel correlations is very challenging. Therefore, a low-complexity solution for

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Publication Date
Fri Dec 28 2018
Journal Name
Iraqi Postgraduate Medical Journal
Recurrent Pneumonia in Children at a Tertiary–Pediatric Hospital in Baghdad
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MK Al-Janabi, NA Nasir, RK Jaber, AO Oleiwe, Iraqi Postgraduate Medical Journal, 2018 - Cited by 7

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Publication Date
Fri Jul 29 2022
Journal Name
Research Journal Of Pharmacy And Technology
Rifampicin versus Doxycycline in Prevention of recurrent Boils (A Comparative Therapeutic Study)
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Background: Suffering from recurrent boils (furunclosis) is a common problem in our locality as it is noticed by many dermatologists especially in association with increasingly hot weather. The most common causative organisms are staphylococci. Objective: The aim of the study was to shed the light upon this problem and compare two systemic therapeutic agents for the prevention of recurrence, doxycycline and rifampicin. Patient and method: One hundred thirty-five (135) Patients with recurrent boils from Al-Yarmouk teaching hospital dermatology outpatient department were included in this study; age ranged from 10 to 64 years old and out of total patients 32 were males and 103 were females. Patients were assessed by full history and cl

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