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Optimal hybrid type-3 fuzzy controller for horizontal axis wind turbines: Comparative study
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The blade pitch angle (BPA) controller is key factor to improve the power generation of wind turbine (WT). Due to the aerodynamic structural behavior of the rotor blades, wind turbine system performance is influenced by pitch angle and environmental conditions such as wind speed, which fluctuate throughout the day. Therefore, to overcome the pitch angle control (PAC) problem, high wind speed conditions, and due to type-1 and type-2 fuzzy logic limitations for handling high levels of uncertainty, the newly proposed optimal hybrid type-3 fuzzy logic controller has been applied and compared since type-3 fuzzy controllers utilize three-dimensional membership functions, unlike type-2 and type-1 fuzzy logic controllers. In this paper six different controllers are applied and compared for BPA in WT: type-1 fuzzy logic controller (T1-FLC), interval type-2 fuzzy logic controller (IT2-FLC), interval type-3 fuzzy logic controller (IT3-FLC), optimal hybrid type-1 fuzzy-PID controller (HT1-FPIDC), optimal hybrid type-2 fuzzy-PID controller (HT2-FPIDC), and optimal hybrid type-3 fuzzy-PID controller (HT3-FPIDC). The comparison between Mamdani and Sugeno fuzzy inference systems (FIS) has been applied to find the best inference system. Genetic Algorithm (GA) and Particle swarm optimization (PSO) are used to find the optimal tuning of PID parameters. The results of the 500-kw horizontal axis wind turbine show that Sugeno FIS has higher stability in output power generation than Mamdani FIS. Also, optimal HT3-FPIDC based on Mamdani FIS with PSO provides 19.74 % lower absolute summation error (ASE) than Sugeno FIS in optimal HT2-FLC with PSO and 39.03 % lower ASE than optimal HT1-FLC based on Sugeno FIS with PSO. Finally, the proposed optimal HT3-FPIDC based on PSO and Mamdani FIS provides the optimal results in terms of consistent output power generation at rated value.

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Publication Date
Tue Oct 16 2018
Journal Name
Springer Science And Business Media Llc
MOGSABAT: a metaheuristic hybrid algorithm for solving multi-objective optimisation problems
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Publication Date
Mon Jan 01 2024
Journal Name
Fusion: Practice And Applications
A Hybrid Meta-Heuristic Approach for Test Case Prioritization and Optimization
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The application of the test case prioritization method is a key part of system testing intended to think it through and sort out the issues early in the development stage. Traditional prioritization techniques frequently fail to take into account the complexities of big-scale test suites, growing systems and time constraints, therefore cannot fully fix this problem. The proposed study here will deal with a meta-heuristic hybrid method that focuses on addressing the challenges of the modern time. The strategy utilizes genetic algorithms alongside a black hole as a means to create a smooth tradeoff between exploring numerous possibilities and exploiting the best one. The proposed hybrid algorithm of genetic black hole (HGBH) uses the

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Publication Date
Thu Dec 16 2021
Journal Name
Translational Vision Science & Technology
A Hybrid Deep Learning Construct for Detecting Keratoconus From Corneal Maps
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Publication Date
Thu Feb 01 2018
Journal Name
Journal Of Engineering
Upgrading of Alum Preparation and Dosing Unit for Sharq Dijla Water Treatment Plant by Using Programmable Logic Controller System
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One of the important units in Sharq Dijla Water Treatment Plant (WTP) first and second extensions are the alum solution preparation and dosing unit. The existing operation of this unit accomplished manually starting from unloading the powder alum in the preparation basin and ending by controlling the alum dosage addition through the dosing pumps to the flash mix chambers. Because of the modern trend of monitoring and control the automatic operation of WTPs due to the great benefits that could be gain from optimum equipment operation, reducing the operating costs and human errors. This study deals with how to transform the conventional operation to an automatic monitoring and controlling system depending on a Programmable

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Publication Date
Tue Sep 01 2009
Journal Name
2009 5th International Conference On Wireless Communications, Networking And Mobile Computing
Cooperation Spectrum Sensing Using Optimal Joint Detecting
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In cognitive radio networks, there are two important probabilities; the first probability is important to primary users called probability of detection as it indicates their protection level from secondary users, and the second probability is important to the secondary users called probability of false alarm which is used for determining their using of unoccupied channel. Cooperation sensing can improve the probabilities of detection and false alarm. A new approach of determine optimal value for these probabilities, is supposed and considered to face multi secondary users through discovering an optimal threshold value for each unique detection curve then jointly find the optimal thresholds. To get the aggregated throughput over transmission

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Publication Date
Sun Jan 01 2023
Journal Name
Physical Mesomechanics Of Condensed Matter: Physical Principles Of Multiscale Structure Formation And The Mechanisms Of Nonlinear Behavior: Meso2022
Optimal control strategy applied to diabetes model
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Publication Date
Mon Jun 30 2025
Journal Name
Acta Logistica
A business continuity-based framework for risk management in smart supply chains: a fuzzy multi-criteria decision-making approach
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The aim of this study is to develop a novel framework for managing risks in smart supply chains by enhancing business continuity and resilience against potential disruptions. This research addresses the growing uncertainty in supply chain environments, driven by both natural phenomena-such as pandemics and earthquakes—and human-induced events, including wars, political upheavals, and societal transformations. Recognizing that traditional risk management approaches are insufficient in such dynamic contexts, the study proposes an adaptive framework that integrates proactive and remedial measures for effective risk mitigation. A fuzzy risk matrix is employed to assess and analyze uncertainties, facilitating the identification of disr

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Publication Date
Fri Apr 21 2023
Journal Name
Aip Conference Proceedings
Study the contrast of thermal expansion behavior for PMMA denture base, single and hybrid reinforced using the thermomechanical analysis technique (TMA)
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This research investigated the effect of adding two groups of reinforcement materials, including bioactive materials Hydroxyapatite (HA) and halloysite nanoclay and bioinert materials Alumina (AL2O3) and Zirconia (ZrO2), each of them with various weight ratios (1,2,3,4 &5)% to the polymer matrix PMMA. The best ratios were selected, and then a hybrid was preparing Composite red from the best ratios from each group. Thermal properties, including thermal conductivity and Thermomechanical Analysis (TMA) technology, have been studied. The results showed that adding 3% Hydroxyapatite (HA) and 5% halloysite nanoclay to the polymethacrylate (PMMA) mer leads to an increase in thermal conductivity. It was also found from the Thermomechanical Analysis

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Publication Date
Tue Nov 01 2022
Journal Name
Alexandria Engineering Journal
Batch and continuous study of one-step sustainable green graphene sand hybrid synthesized from Date-syrup for remediation of contaminated groundwater
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Publication Date
Wed Jan 01 2020
Journal Name
Periodicals Of Engineering And Natural Sciences (pen)
Estimating the reliability function of the asymmetrical hybrid parallel-series system: Applied study at the state company for vegetable oils industry
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The research studied and analyzed the hybrid parallel-series systems of asymmetrical components by applying different experiments of simulations used to estimate the reliability function of those systems through the use of the maximum likelihood method as well as the Bayes standard method via both symmetrical and asymmetrical loss functions following Rayleigh distribution and Informative Prior distribution. The simulation experiments included different sizes of samples and default parameters which were then compared with one another depending on Square Error averages. Following that was the application of Bayes standard method by the Entropy Loss function that proved successful throughout the experimental side in finding the reliability fun

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