Search Results - (( panel optimization method algorithm ) OR ( pattern selection method algorithm ))*
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Optimization of stiffened panel fatigue life by using finite element analysis
Published 2020“…Three optimization methods: screening, multi-objective genetic algorithm and adaptive multi-objective algorithm were adopted in this study. …”
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Hybrid MPPT algorithm for mismatch photovoltaic panel application / Muhammad Iqbal Mohd Zakki
Published 2019“…MATLAB/Simulink is used to develop, test, optimize, and verify the proposed hybrid MPPT algorithm, and PSO-PID tuning method, before embedded in the MPPT system for the hardware implementation as a research product. …”
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Optimization variation for multiple heuristic approaches in solar tracking
Published 2023Subjects: “…Genetic algorithm…”
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Performance analysis of PSO MPPT for photovoltaic (PV) system during irradiance changes / Kharismi Burhanudin
Published 2018“…Particle swarm optimization is soft computing methods which follow the bird swarm to track maximum power from PV panel. …”
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Naive Bayes-guided bat algorithm for feature selection
Published 2023“…The performance of the proposed feature selection algorithm was investigated using twelve benchmark datasets from different domains and was compared to three other well-known feature selection algorithms. …”
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Performance analyses of various photovoltaic power plant based on local spectral irradiances in Malaysia using genetic algorithm
Published 2023“…Besides, the genetic algorithm has showed that it is an effective and efficient way to perform estimation of optimal tilt angle and orientation angle for solar sites with genetic algorithm as it is able to produce correct and accurate result in a short amount of time.…”
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Final Year Project / Dissertation / Thesis -
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Optimization of a reliable grid-connected PV-based power plant
Published 2023“…Maximum power point tracking (MPPT) has been used in this project in optimizing the PV system. One of the methods of the MPPT technique which is Perturb and Observe (P&O) algorithm, easy to implement and has efficient performance in solving the optimization problem. …”
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Proceeding Paper -
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Development of a new robust hybrid automata algorithm based on surface electromyography (SEMG) signal for instrumented wheelchair control
Published 2020“…This method would be a control method to activate power assist system and selected based on conditions set in the algorithm. …”
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New Fast Block Matching Algorithm Using New Hybrid Search Pattern And Strategy To Improve Motion Estimation Process In Video Coding Technique
Published 2016“…These 6 algorithms are divided into 3 main methods namely Method A, Method B, and Method C depending on their search patterns and strategies. …”
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Analysis and evaluation of various aspects of solar radiation in the Palestinian territories
Published 2023“…It was also found that changing the tilt angle of the PV panels quarterly (optimized on seasonally basis) increases energy yield by 3.4% when compared with fixing this tilt angle at yearly optimized value. …”
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Variable block based motion estimation using hexagon diamond full search algorithm (HDFSA) via block subtraction technique
Published 2015“…The variable block matching developed based on four stages which is the video and frame selection, threshold calculation, block size selection and search pattern. …”
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Multi-objective optimization of stand-alone hybrid renewable energy system by genetic algorithm
Published 2013“…Among these methods, Genetic Algorithm and Particle Swarm Optimization are known as two most effective methods for HRESs. …”
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Fuzzy based BSA optimization for maximum power point tracking controller performance evaluation
Published 2023Conference Paper -
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Application of the bees algorithm to the selection features for manufacturing data
Published 2007“…The Bees Algorithm is employed to select an optimal set of features for a particular pattern classification task. …”
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Conference or Workshop Item -
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A comparative study of clonal selection algorithm for effluent removal forecasting in septic sludge treatment plant
Published 2023“…Algorithms; Artificial intelligence; Biochemical oxygen demand; Bioinformatics; Developing countries; Effluent treatment; Effluents; Forecasting; Least squares approximations; Oxygen; Pattern recognition; Support vector machines; Water quality; Biological oxygen demand; Clonal selection algorithms; Least-square support vector machines; Sludge treatment plants; Total suspended solids; Chemical oxygen demand; oxygen; sewage; algorithm; clone; comparative study; effluent; least squares method; nonlinearity; pattern recognition; simulation; sludge; water treatment; activated sludge; algorithm; Article; biochemical oxygen demand; chemical oxygen demand; clonal selection algorithm; comparative study; computer simulation; effluent; forecasting; pattern recognition; prediction; regression analysis; septic sludge treatment plant; sludge treatment; statistical model; support vector machine; suspended particulate matter; waste water treatment plant; chemistry; procedures; sewage; theoretical model; Algorithms; Biological Oxygen Demand Analysis; Forecasting; Least-Squares Analysis; Models, Theoretical; Sewage; Support Vector Machines; Waste Disposal, Fluid…”
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Modeling and analysis of the impact of information and communication technology on household consumption expenditure in different regions
Published 2022“…Based on the panel data of cities and towns in China, by using the generalized estimation method of a dynamic panel, through the construction of regional household consumption expenditure evaluation models, optimize the impact evaluation algorithm of household consumption expenditure in different regions, standardize critic indicators, and build the impact modeling of household consumption expenditure in combination with relevant algorithms such as the Engel coefficient. …”
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An ensemble learning method for spam email detection system based on metaheuristic algorithms
Published 2015“…In comparison to different single algorithms for feature selection,experimental results show that the proposed ensemble method is able to reduce dimensionality, the number of irrelevant features and produce reasonable classifier accuracy. …”
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