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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 Nov 01 2018
Journal Name
Journal Of Economics And Administrative Sciences
The research is based on a thesis not discussed: Test the strategy of the General Organization based on the model Wichler and Bakov A case study at the Iraqi Ministry of Interior
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The study aimed at identifying the strategic gaps in the actual reality of the management of public organizations investigated to determine the strategy used based on the study model. The study relied on the variable of the general organization strategy in its dimensions (the general organization strategy, the organization's political strategy and the defense strategy of the organization) The sample of the study was (General Directorate of Traffic, Civil Status Directorate and Civil Defense Directorate), formations affiliated to the Ministry of the Interior, for the importance of the activity carried out by these public organizations by providing them In order to translate the answers into a quantitative expression in the analysi

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Publication Date
Wed Jul 12 2023
Journal Name
Energies
Finite Time Disturbance Observer Based on Air Conditioning System Control Scheme
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A novel robust finite time disturbance observer (RFTDO) based on an independent output-finite time composite control (FTCC) scheme is proposed for an air conditioning-system temperature and humidity regulation. The variable air volume (VAV) of the system is represented by two first-order mathematical models for the temperature and humidity dynamics. In the temperature loop dynamics, a RFTDO temperature (RFTDO-T) and an FTCC temperature (FTCC-T) are designed to estimate and reject the lumped disturbances of the temperature subsystem. In the humidity loop, a robust output of the FTCC humidity (FTCC-H) and RFTDO humidity (RFTDO-H) are also designed to estimate and reject the lumped disturbances of the humidity subsystem. Based on Lyapunov theo

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Publication Date
Thu Feb 01 2018
Journal Name
Journal Of Economics And Administrative Sciences
Evaluation of Common Stocks Using The Fama-French Five Factor Model An Applied Study in The Iraq Stock Exchange
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     The process of stocks evaluating considered as a one of challenges for the financial analysis, since the evaluating focuses on define the current value for the cash flows which the shareholders expected to have. Due to the importance of this subject, the current research aims to choose Fama & French five factors Model to evaluate the common stocks to define the Model accuracy in Fama& French for 2014. It has been used factors of volume, book value to market value, Profitability and investment, in addition to Beta coefficient which used in capital assets pricing Model as a scale for Fama & French five factors Model. The research sample included 11 banks listed in Iraq stock market which have me

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Publication Date
Sun Jan 01 2023
Journal Name
Ssrn Electronic Journal
Increasing Safety in Highways Transit Systems by Using Ethical Artificial Intelligence AI
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“Smart city” projects have become fully developed and are actively using video analytics. Our study looks at how video analytics from surveillance cameras can help manage urban areas, making the environment safer and residents happier. Every year hundreds of people fall on subway and railway lines. The causes of these accidents include crowding, fights, sudden health problems such as dizziness or heart attacks, as well as those who intentionally jump in front of trains. These accidents may not cause deaths, but they cause delays for tens of thousands of passengers. Sometimes passers-by have time to react to the event and try to prevent it, or contact station personnel, but computers can react faster in such situations by using ethical

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Publication Date
Tue Oct 19 2021
Journal Name
International Journal Of Online And Biomedical Engineering (ijoe)
Object Tracking Using Adaptive Diffusion Flow Active Model
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Object tracking is one of the most important topics in the fields of image processing and computer vision. Object tracking is the process of finding interesting moving objects and following them from frame to frame. In this research, Active models–based object tracking algorithm is introduced. Active models are curves placed in an image domain and can evolve to segment the object of interest. Adaptive Diffusion Flow Active Model (ADFAM) is one the most famous types of Active Models. It overcomes the drawbacks of all previous versions of the Active Models specially the leakage problem, noise sensitivity, and long narrow hols or concavities. The ADFAM is well known for its very good capabilities in the segmentation process. In this

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Publication Date
Wed Jan 01 2020
Journal Name
Materials Science And Engineering
Fresh and Hardened Properties of Nano Self-Compacting Concrete with Micro and Nano Silica
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Abstract<p>Self-compacting concrete (SCC) has undergone a remarkable evolution recently based on the results from several studies that have indicated the chain of benefits SCC provides. Micro and nano materials used as mineral additives in SCC offer several high-performance properties, and this research studies the effects of micro silica (MS) (10%, used as a reference) and colloidal nano-silica (CNS) (2.5%, 5%, 7.5%, and 10%) on the fresh and hardened properties of SCC. All mixtures were estimated using flow, L-box, and V-funnel tests to examine workability and compressive strength, modulus of elasticity and tensile strength as hardened properties. The use of CNS increased the overall compressi</p> ... Show More
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Publication Date
Fri Oct 12 2018
Journal Name
International Journal Of Dynamics And Control
Decentralized adaptive partitioned approximation control of high degrees-of-freedom robotic manipulators considering three actuator control modes
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Publication Date
Mon Jul 18 2022
Journal Name
Ieee Access
Moderately Multispike Return Neural Network for SDN Accurate Traffic Awareness in Effective 5G Network Slicing
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Due to the huge variety of 5G services, Network slicing is promising mechanism for dividing the physical network resources in to multiple logical network slices according to the requirements of each user. Highly accurate and fast traffic classification algorithm is required to ensure better Quality of Service (QoS) and effective network slicing. Fine-grained resource allocation can be realized by Software Defined Networking (SDN) with centralized controlling of network resources. However, the relevant research activities have concentrated on the deep learning systems which consume enormous computation and storage requirements of SDN controller that results in limitations of speed and accuracy of traffic classification mechanism. To fill thi

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Scopus (15)
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Publication Date
Fri Jan 01 2021
Journal Name
International Journal Of Agricultural And Statistical Sciences
DYNAMIC MODELING FOR DISCRETE SURVIVAL DATA BY USING ARTIFICIAL NEURAL NETWORKS AND ITERATIVELY WEIGHTED KALMAN FILTER SMOOTHING WITH COMPARISON
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Survival analysis is widely applied in data describing for the life time of item until the occurrence of an event of interest such as death or another event of understudy . The purpose of this paper is to use the dynamic approach in the deep learning neural network method, where in this method a dynamic neural network that suits the nature of discrete survival data and time varying effect. This neural network is based on the Levenberg-Marquardt (L-M) algorithm in training, and the method is called Proposed Dynamic Artificial Neural Network (PDANN). Then a comparison was made with another method that depends entirely on the Bayes methodology is called Maximum A Posterior (MAP) method. This method was carried out using numerical algorithms re

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Publication Date
Wed Jun 01 2011
Journal Name
Journal Of Economics And Administrative Sciences
Selection of the initial value of the time series generating the first-order self-regression model in simulation modeAnd their impact on the accuracy of the model
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In this paper, compared eight methods for generating the initial value and the impact of these methods to estimate the parameter of a autoregressive model, as was the use of three of the most popular methods to estimate the model and the most commonly used by researchers MLL method, Barg method  and the least squares method and that using the method of simulation model  first order autoregressive through the design of a number of simulation experiments and the different sizes of the samples.

                  

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