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Optimal Hybrid Fuzzy PID for Pitch Angle Controller in Horizontal Axis Wind Turbines
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Wind turbine (WT) is now a major renewable energy resource used in the modern world. One of the most significant technologies that use the wind speed (WS) to generate electric power is the horizontal-axis wind turbine. In order to enhance the output power over the rated WS, the blade pitch angle (BPA) is controlled and adjusted in WT. This paper proposes and compares three different controllers of BPA for a 500-kw WT. A PID controller (PIDC), a fuzzy logic controller (FLC) based on Mamdani and Sugeno fuzzy inference systems (FIS), and a hybrid fuzzy-PID controller (HFPIDC) have been applied and compared. Furthermore, Genetic Algorithm (GA) and Particle swarm optimization (PSO) have been applied and compared in order to identify the optimal PID parameters (kp, ki, kd). The objective of GA and PSO is minimized the error signal in output power based on actual WS. The results for three different controllers show that the optimal hybrid FPIDC based on the Sugeno inference system with PSO produces the optimal results regard to reduce the error signal and stable output power under actual WS.

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Publication Date
Sat Dec 17 2022
Journal Name
Applied Sciences
A Hybrid Artificial Intelligence Model for Detecting Keratoconus
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Machine learning models have recently provided great promise in diagnosis of several ophthalmic disorders, including keratoconus (KCN). Keratoconus, a noninflammatory ectatic corneal disorder characterized by progressive cornea thinning, is challenging to detect as signs may be subtle. Several machine learning models have been proposed to detect KCN, however most of the models are supervised and thus require large well-annotated data. This paper proposes a new unsupervised model to detect KCN, based on adapted flower pollination algorithm (FPA) and the k-means algorithm. We will evaluate the proposed models using corneal data collected from 5430 eyes at different stages of KCN severity (1520 healthy, 331 KCN1, 1319 KCN2, 1699 KCN3 a

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Publication Date
Tue Dec 21 2021
Journal Name
Mendel
Hybrid Deep Learning Model for Singing Voice Separation
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Monaural source separation is a challenging issue due to the fact that there is only a single channel available; however, there is an unlimited range of possible solutions. In this paper, a monaural source separation model based hybrid deep learning model, which consists of convolution neural network (CNN), dense neural network (DNN) and recurrent neural network (RNN), will be presented. A trial and error method will be used to optimize the number of layers in the proposed model. Moreover, the effects of the learning rate, optimization algorithms, and the number of epochs on the separation performance will be explored. Our model was evaluated using the MIR-1K dataset for singing voice separation. Moreover, the proposed approach achi

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Publication Date
Thu Oct 25 2018
Journal Name
Journal Of Economics And Administrative Sciences
Find the fuzzy maximum flow of Imam Kadhimen visitors using fuzzy dynamic programming University of Baghdad - Faculty of Administration and Economics
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    Baghdad and the other Iraqis provinces have witnessed many   of celebrations which have the significant effect on the souls of Arabic and Islamic people in general , and Iraqi people, especially the birthday and death of two al-kadhimen Imams(peace upon them) and others .From here the researcher begin to study the visiting of imam kadhimen (peace upon him) on 25 Rajab the commemoration of his sacrifice, simply because have implications of religious, ideological and cultural sectors which represents in finding the greatest flow of visitors .the problem of research appeared due to the clear difference in number of visitors during one day, beside the significant increase in number of visitors  throu

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Publication Date
Sun Jun 01 2025
Journal Name
Journal Of Physics: Conference Series
Optimal Variational Iteration Method for Solving Nonlinear Ordinary Differential Equations Appeared in Engineering and Applied Sciences
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Physics and applied mathematics form the basis for understanding natural phenomena using differential equations depicting the flow in porous media, the motion of viscous liquids, and the propagation of waves. These equations provide a thorough study of physical processes, enhancing the understanding of complex applications in engineering, technology, and medicine. This paper presents novel approximate solutions for the Darcy-Brinkmann-Forchheimer moment equation, the Blasius equation and the FalknerSkan equation with initial / boundary conditions by using two iterative methods: the variational iteration method and the optimal variational iteration method. The variational iteration method is effectively developed by adding a control paramete

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Publication Date
Wed Dec 01 2021
Journal Name
Baghdad Science Journal
Improvement of the Fault Tolerance in IoT Based Positioning Systems by Applying for Redundancy in the Controller Layer
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In recent years, the positioning applications of Internet-of-Things (IoT) based systems have grown increasingly popular, and are found to be useful in tracking the daily activities of children, the elderly and vehicle tracking. It can be argued that the data obtained from GPS based systems may contain error, hence taking these factors into account, the proposed method for this study is based on the application of IoT-based positioning and the replacement of using IoT instead of GPS.  This cannot, however, be a reason for not using the GPS, and in order to enhance the reliability, a parallel combination of the modern system and traditional methods simultaneously can be applied. Although GPS signals can only be accessed in open spaces, GP

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Publication Date
Mon Nov 20 2028
Journal Name
Iraqi Journal Of Market Research And Consumer Protection
DETERMINATION OF OPTIMAL CONDITIONS FOR CAROTENOIDS PRODUCTION BY CHEMICAL MUTANAT LOCAL ISOLATE RHODOTORUL MUCILAGENOSA M.: DETERMINATION OF OPTIMAL CONDITIONS FOR CAROTENOIDS PRODUCTION BY CHEMICAL MUTANAT LOCAL ISOLATE RHODOTORUL MUCILAGENOSA M.
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The aim of this study was to increasing natural carotenoides production by a locally isolate Rodotorula mucilagenosa M. by determination of the optimal conditions for growth and production of this agents, for encouragest to use it in food application permute artificial pigments which harmfull for consumer health and envieronmental. The optimal condition of carotenoides production from Rhodotorula mucilaginosa M were studied. The results shows the best carbon and nitrogen source were glucose and yeast extract. The carotenoids a mount production was 47430 microgram ̸ litter and 47460 microgram ̸ litter, respectively, and the optimum temperature was 30°C, PH 6, that the carotenoides a mount was 47470 microgram ̸ litter and 47670 microgr

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Publication Date
Wed Sep 01 2021
Journal Name
Baghdad Science Journal
Fuzzy-assignment Model by Using Linguistic Variables
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      This work addressed the assignment problem (AP) based on fuzzy costs, where the objective, in this study, is to minimize the cost. A triangular, or trapezoidal, fuzzy numbers were assigned for each fuzzy cost. In addition, the assignment models were applied on linguistic variables which were initially converted to quantitative fuzzy data by using the Yager’sorankingi method. The paper results have showed that the quantitative date have a considerable effect when considered in fuzzy-mathematic models.

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Publication Date
Thu Sep 13 2018
Journal Name
Baghdad Science Journal
Dynamic Routing Method over Hybrid SDN for Flying Ad Hoc Networks
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Due to the high mobility and dynamic topology of the FANET network, maintaining communication links between UAVs is a challenging task. The topology of these networks is more dynamic than traditional mobile networks, which raises challenges for the routing protocol. The existing routing protocols for these networks partly fail to detect network topology changes. Few methods have recently been proposed to overcome this problem due to the rapid changes of network topology. We try to solve this problem by designing a new dynamic routing method for a group of UAVs using Hybrid SDN technology (SDN and a distributed routing protocol) with a highly dynamic topology. Comparison of the proposed method performance and two other algorithms is simula

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Publication Date
Wed Sep 01 2021
Journal Name
Journal Of Engineering
Spike neural network as a controller in SDN network
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The paper proposes a methodology for predicting packet flow at the data plane in smart SDN based on the intelligent controller of spike neural networks(SNN). This methodology is applied to predict the subsequent step of the packet flow, consequently reducing the overcrowding that might happen. The centralized controller acts as a reactive controller for managing the clustering head process in the Software Defined Network data layer in the proposed model. The simulation results show the capability of Spike Neural Network controller in SDN control layer to improve the (QoS) in the whole network in terms of minimizing the packet loss ratio and increased the buffer utilization ratio.

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Publication Date
Tue Mar 26 2024
Journal Name
World Electric Vehicle Journal
Fast Finite-Time Composite Controller for Vehicle Steer-by-Wire Systems with Communication Delays
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The modern steer-by-wire (SBW) systems represent a revolutionary departure from traditional automotive designs, replacing mechanical linkages with electronic control mechanisms. However, the integration of such cutting-edge technologies is not without its challenges, and one critical aspect that demands thorough consideration is the presence of nonlinear dynamics and communication network time delays. Therefore, to handle the tracking error caused by the challenge of time delays and to overcome the parameter uncertainties and external perturbations, a robust fast finite-time composite controller (FFTCC) is proposed for improving the performance and safety of the SBW systems in the present article. By lumping the uncertainties, parameter var

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