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A comparative study of evolutionary algorithms and adapting control parameters for estimating the parameters of a single-diode photovoltaic module's model
Published 2023“…Algorithms; Diodes; Errors; Iterative methods; Least squares approximations; Mean square error; Optimization; Parameter estimation; Parameter extraction; Photovoltaic cells; Coefficient of determination; Differential Evolution; Electromagnetism-like algorithm; Hybrid evolutionary algorithm; Photovoltaic; Photovoltaic modules; Root mean square errors; Single-diode models; Evolutionary algorithms; algorithm; comparative study; electromagnetic method; estimation method; experimental design; numerical method; parameterization; performance assessment; photovoltaic system…”
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Parameters extraction of double diode photovoltaic module's model based on hybrid evolutionary algorithm
Published 2023“…Algorithms; Diodes; Errors; Extraction; Iterative methods; Mean square error; Optimization; Parameter estimation; Parameter extraction; Photovoltaic cells; Differential evolution algorithms; Diode modeling; Electromagnetism-like algorithm; Fast convergence speed; Hybrid evolutionary algorithm; IV characteristics; Photovoltaic model; Root mean square errors; Evolutionary algorithms…”
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Evolution Performance of Symbolic Radial Basis Function Neural Network by Using Evolutionary Algorithms
Published 2023“…The SRBFNN’s objective function that corresponds to Satisfiability logic programming can be minimized by different algorithms, including Genetic Algorithm (GA), Evolution Strategy Algorithm (ES), Differential Evolution Algorithm (DE), and Evolutionary Programming Algorithm (EP). …”
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Time series predictive analysis based on hybridization of meta-heuristic algorithms
Published 2018“…The identified meta-heuristic methods namely Moth-flame Optimization (MFO), Cuckoo Search algorithm (CSA), Artificial Bee Colony (ABC), Firefly Algorithm (FA) and Differential Evolution (DE) are individually hybridized with a well-known machine learning technique namely Least Squares Support Vector Machines (LS-SVM). …”
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5
Evolution Performance of Symbolic Radial Basis Function Neural Network by Using Evolutionary Algorithms
Published 2023“…The SRBFNN’s objective function that corresponds to Satisfiability logic programming can be minimized by different algorithms, including Genetic Algorithm (GA), Evolution Strategy Algorithm (ES), Differential Evolution Algorithm (DE), and Evolutionary Programming Algorithm (EP). …”
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Evolution Performance of Symbolic Radial Basis Function Neural Network by Using Evolutionary Algorithms
Published 2023“…The SRBFNN’s objective function that corresponds to Satisfiability logic programming can be minimized by different algorithms, including Genetic Algorithm (GA), Evolution Strategy Algorithm (ES), Differential Evolution Algorithm (DE), and Evolutionary Programming Algorithm (EP). …”
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Evolution Performance of Symbolic Radial Basis Function Neural Network by Using Evolutionary Algorithms
Published 2023“…The SRBFNN’s objective function that corresponds to Satisfiability logic programming can be minimized by different algorithms, including Genetic Algorithm (GA), Evolution Strategy Algorithm (ES), Differential Evolution Algorithm (DE), and Evolutionary Programming Algorithm (EP). …”
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Evolution Performance of Symbolic Radial Basis Function Neural Network by Using Evolutionary Algorithms
Published 2023“…The SRBFNN’s objective function that corresponds to Satisfiability logic programming can be minimized by different algorithms, including Genetic Algorithm (GA), Evolution Strategy Algorithm (ES), Differential Evolution Algorithm (DE), and Evolutionary Programming Algorithm (EP). …”
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Evolution Performance of Symbolic Radial Basis Function Neural Network by Using Evolutionary Algorithms
Published 2023“…The SRBFNN’s objective function that corresponds to Satisfiability logic programming can be minimized by different algorithms, including Genetic Algorithm (GA), Evolution Strategy Algorithm (ES), Differential Evolution Algorithm (DE), and Evolutionary Programming Algorithm (EP). …”
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10
Time series predictive analysis based on hybridization of meta-heuristic algorithms
Published 2018“…The identified meta-heuristic methods namely Moth-flame Optimization (MFO), Cuckoo Search algorithm (CSA), Artificial Bee Colony (ABC), Firefly Algorithm (FA) and Differential Evolution (DE) are individually hybridized with a well-known machine learning technique namely Least Squares Support Vector Machines (LS-SVM). …”
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A hyper-heuristic based strategy for image segmentation using multilevel thresholding
Published 2025“…EMCQ uses four low-level heuristic sets adopted from the teaching learning-based optimisation (TLBO) algorithm, flower pollination algorithm (FPA), genetic algorithm (GA), and Jaya algorithm. …”
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A hyper-heuristic based strategy for image segmentation using multilevel thresholding
Published 2025“…EMCQ uses four low-level heuristic sets adopted from the teaching learning-based optimisation (TLBO) algorithm, flower pollination algorithm (FPA), genetic algorithm (GA), and Jaya algorithm. …”
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Chiller power consumption forecasting for commercial building based on hybrid convolution neural networks-long short-term memory model with barnacles mating optimizer
Published 2025“…The study compares the proposed CNN-LSTM-BMO against other metaheuristic optimization algorithms, including Genetic Algorithm (GA), Particle Swarm Optimization (PSO), Ant Colony Optimization (ACO), and Differential Evolution (DE). …”
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Development of an islanding detection scheme based on combination of slantlet transform and ridgelet probabilistic neural network in distributed generation
Published 2019“…Furthermore, to evaluate the efficiency of the proposed modified differential evolution for the training of ridgelet probabilistic neural network, four statistical search techniques, namely, particle swarm optimization, genetic algorithm, simulated angling, and classical differential evolution are used and their results are compared. …”
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Dynamic transmit antenna shuffling scheme for hybrid multiple-input multiple-output in layered architecture
Published 2010“…The computational complexity (total number of arithmetic operations) of proposed LC-QR algorithm is significantly lower than the conventional QR decomposition, zero-forcing (ZF) and minimum mean square error (MMSE) detection algorithm. …”
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Ant colony optimization and genetic algorithm models for suspended sediment discharge estimation for gorgan-river, Iran
Published 2011“…The training and testing data sets were chosen based on the K-fold method of cross validation to find the optimal classifier. …”
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Spatial domain image steganography based on right most digit replacement and parity bit differencing / Mehdi Hussain
Published 2017“…Results from the above evaluations have proven that proposed methods achieved the optimal performance regarding general steganography objective/challenges. …”
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Application of swarm intelligence optimization on bio-process problems / Mohamad Zihin Mohd Zain
Published 2018“…The proposed method is tested on 10 multi-objective benchmark problems of CEC 2009 and compared with four metaheuristics: Multi-Objective Grey Wolf Optimizer (MOGWO), Multi-Objective Evolutionary Algorithm Based on Decomposition (MOEA/D), Multi-Objective Differential Evolution (MODE) and MOPSO. …”
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Parameter Estimation Using Improved Differential Evolution And Bacterial Foraging Algorithms To Model Tyrosine Production In Mus Musculus(Mouse)
Published 2015“…The hybrid of Differential Evolution algorithm with Kalman Filtering and Bacterial Foraging algorithm is a novel global optimisation method implemented to obtain the best kinetic parameter value. …”
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A new modified differential evolution algorithm scheme-based linear frequency modulation radar signal de-noising
Published 2015“…The main intention of this study was to investigate the development of a new optimization technique based on the differential evolution (DE) algorithm, for the purpose of linear frequency modulation radar signal de-noising. …”
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