Search Results - (( using evolution method algorithm ) OR ( parameter estimation study algorithm ))
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Extraction of photovoltaic module model's parameters using an improved hybrid differential evolution/electromagnetism-like algorithm
Published 2023“…Algorithms; Evolutionary algorithms; Mean square error; Optimization; Parameter estimation; Photovoltaic cells; Coefficient of determination; DEAM; Five parameters; Hybrid differential evolution; Improved differential evolutions; IV characteristics; Photovoltaic modules; Root mean square errors; Iterative methods; algorithm; artificial intelligence; electromagnetic method; error analysis; experimental study; photovoltaic system…”
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Robust Portfolio Mean-Variance Optimization for Capital Allocation in Stock Investment Using the Genetic Algorithm: A Systematic Literature Review
Published 2024journal::journal article -
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On a new transmuted three-parameter lindley distribution and its applications
Published 2024“…The statistical properties of the TTHPLD model, which are based on moments, order statistics, hazard rate functions, reliability functions, and Renyi entropy, have been studied. Moreover, the maximum likelihood estimators (MLEs) of the TTHPLD are obtained via differential evolution algorithms, and a simulation study is conducted to evaluate the consistency of the MLEs. …”
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Vibration-based structural damage detection and system identification using wavelet multiresolution analysis / Seyed Alireza Ravanfar
Published 2017“…This resulted in the high accuracy of the damage detection algorithm. The second proposed method seeks to identify damage in the structural parameters of linear and nonlinear systems. …”
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State of charge estimation for electric vehicles using random forest
Published 2024“…This study applies a Random Forest (RF) machine learning algorithm to improve SOC estimation. …”
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Ant colony optimization and genetic algorithm models for suspended sediment discharge estimation for gorgan-river, Iran
Published 2011“…Three methods based on the dividing of used data into monthly, seasonally and annually time bases were used by each model to identify the relationship between suspended sediment discharge and flow discharge for estimate the suspended sediment. …”
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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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Performance evaluation of hybrid adaptive neuro-fuzzy inference system models for predicting monthly global solar radiation
Published 2018“…The proposed hybrid models include particle swarm optimization, genetic algorithm and differential evolution. To evaluate the capability and efficiency of the proposed models, several statistical indicators such as; root mean square error, co-efficient of determination and mean absolute bias error are used. …”
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Parameter extraction of photovoltaic module using hybrid evolutionary algorithm
Published 2023Conference Paper -
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Estimation in spot welding parameters using genetic algorithm
Published 2007“…In this study, parameter of spot welding estimate using computer simulation. …”
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LASSO-type estimations for threshold autoregressive and heteroscedastic time series models.
Published 2020“…Furthermore, the ensemble algorithms of BCD-BEA perform better in terms of correctly estimating the number of thresholds in simulation studies, and in identifying important thresholds in case studies compared to the ensemble algorithms of GLAR-BEA. …”
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Semiparametric inference procedure for the accelarated failure time model with interval-censored data
Published 2019“…A computationally simple two-step iterative algorithm, called estimationapproximation algorithm, is introduced for estimating the parameters of the model on the basis of the rank estimators. …”
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Enhanced segment particle swarm optimization for large-scale kinetic parameter estimation of escherichia coli network model
Published 2021“…However, the large-scale kinetic parameters estimation using optimization algorithms is still not applied to the main metabolic pathway of the E. coli model, and they’re a lack of accuracy result been reported for current parameters estimation using this approach. …”
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An enhanced segment particle swarm optimization algorithm for kinetic parameters estimation of the main metabolic model of Escherichia coli
Published 2020“…In this study, an Enhanced Segment Particle Swarm Optimization algorithm (ESe-PSO) was proposed for kinetic parameters estimation. …”
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Parameter estimation of tapioca starch hydrolysis process: application of least squares and genetic algorithm
Published 2005“…The performance of genetic algorithm (GA) in nonlinear kinetic parameter estimation of topiaca starch hydrolysis was studied and compared with Gauss-Newton method. …”
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Voltage stability margin identification using evolution programming learning algorithm / Zamzuhairi Darus
Published 2003“…This project proposed on an investigation on the voltage stability margin identification using evolution programming learning algorithm. A multilayer feed-forward artificial neural network (ANN) with evolution programming learning algorithm for calculation of voltage stability margins (VSM). …”
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Using the evolutionary mating algorithm for optimizing deep learning parameters for battery state of charge estimation of electric vehicle
Published 2023“…This paper presents the application of a recent metaheuristic algorithm namely Evolutionary Mating Algorithm (EMA) for optimizing the Deep Learning (DL) parameters to estimate the state of charge (SOC) of a battery for an electric vehicle in the real environment. …”
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Parameter Estimation of Lorenz Attractor: A Combined Deep Neural Network and K-Means Clustering Approach
Published 2022“…This research is mainly aimed at introducing a deep learning approach to solve chaotic system parameter estimates like the Lorenz system. The reason for the study is that because of its dynamic instability, the parameter of the chaotic system cannot be easily estimated. …”
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Finite impulse response optimizers for solving optimization problems
Published 2019“…Nonetheless, no study on parameter tuning being carried out for all SKF’s parameters. …”
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