Search Results - (( simulation optimization methods algorithm ) OR ( parameter estimation case algorithm ))
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Fitness-guided particle swarm optimization with adaptive Newton-Raphson for photovoltaic model parameter estimation
Published 2025“…This study introduces a new approach for parameter optimization in the four-diode photovoltaic (PV) model, employing a Dynamic Fitness-Guided Particle Swarm Optimization (DFGPSO) algorithm and Enhanced Newton-Raphson (ENR) method. …”
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Improving the modeling capacity of Volterra model using evolutionary computing methods based on Kalman Smoother adaptive filter
Published 2015“…The first step is combining the forward and backward estimator in the original Volterra model; the second step is reformulating the Volterra model into a state-space model so that the Kalman Smoother (KS) adaptive filter can be used to estimate the kernel coefficients; the third step is optimization of KS parameters using evolutionary computing algorithms such as particle swarm optimization (PSO), genetic algorithm (GA) and artificial bee colony (ABC). …”
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Improving the modeling capacity of Volterra model using evolutionary computing methods based on Kalman smoother adaptive filter
Published 2015“…The first step is combining the forward and backward estimator in the original Volterra model; the second step is reformulating the Volterra model into a state-space model so that the Kalman Smoother (KS) adaptive filter can be used to estimate the kernel coefficients; the third step is optimization of KS parameters using evolutionary computing algorithms such as particle swarm optimization (PSO), genetic algorithm (GA) and artificial bee colony (ABC). …”
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A memory-guided Jaya algorithm to solve multi-objective optimal power flow integrating renewable energy sources
Published 2025“…To ensure fair comparisons, parameter configurations for all algorithms are automated using the parameter tuning tool iterated racing (irace). …”
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Improved genetic algorithm for direct current motor high speed controller implemented on field programmable gate array
Published 2019“…There are many researches have been done to optimize PI controller based evolutionary algorithm, such as Genetic Algorithm (GA). …”
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Modeling and control of a Pico-satellite attitude using Fuzzy Logic Controller
Published 2010“…It is observed that the APFLC showed convincing performance over the entire simulation of the Pico-satellite. Genetic Algorithm (GA) is a computational model inspired by evaluation. …”
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Self-Adaptive Autoreclosing Scheme usingI Artificial Neural Network and Taguchi's Methodology in Extra High Voltage Transmission Systems
Published 2009“…In addition, Taguchi's methodology is employed in optimizing the parameters of each algorithm used for training, and in deciding the number of hidden neurons of the neural network. …”
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Information Theoretic-based Feature Selection for Machine Learning
Published 2018“…Three major factors that determine the performance of a machine learning are the choice of a representative set of features, choosing a suitable machine learning algorithm and the right selection of the training parameters for a specified machine learning algorithm. …”
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Dynamic investment model for the restructed power market in the presence of wind source
Published 2014“…In the third step, the long term optimal investment strategies of the hybrid wind-thermal investor are determined based on the dynamic programming algorithm by considering the long term states of demand growth and fuel price uncertainties. …”
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Parameter estimation of cocomo model using the jaya algorithm for software cost estimation
Published 2019“…The Constructive Cost Model (COCOMO) is a procedural software cost estimation model developed by Barry W. Boehm. In this case, the estimation of value of the COCOMO model parameters are determined for the cost and time estimation of the COCOMO model. …”
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Undergraduates Project Papers -
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Integrated optimal control and parameter estimation algorithms for discrete-time nonlinear stochastic dynamical systems
Published 2011“…The main idea is the integration of optimal control and parameter estimation. In this work, a simplified model-based optimal control model with adjustable parameters is constructed. …”
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An Improved Hybrid of Particle Swarm Optimization and the Gravitational Search Algorithm to Produce a Kinetic Parameter Estimation of Aspartate Biochemical Pathways
Published 2017“…The results show that the proposed algorithm outperformed other standard optimization algorithms in terms of accuracy and near-optimal kinetic parameter estimation. …”
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LASSO-type estimations for threshold autoregressive and heteroscedastic time series models.
Published 2020“…In this thesis, we propose Least Absolute Shrinkage and Selection Operator (LASSO) type estimators to perform simultaneous parameter estimation and model selection for five specific univariate and multivariate time series models, and develop several algorithms to compute these estimators. …”
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UMK Etheses -
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Optimization of turning parameters using genetic algorithm method
Published 2008“…The simulation based on Genetic Algorithm are successful develop and the optimum parameters values are obtained from the simulation.…”
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Undergraduates Project Papers -
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Kalman filter based impedance parameter estimation for transmission line and distribution line
Published 2019“…The positive sequence measurement is use to estimate the positive sequence parameters which will generate inaccurate parameter estimates. …”
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Hybrid firefly and particle swarm optimization algorithm for multi-objective optimal power flow with distributed generation
Published 2022“…This thesis proposes and simulates the three novel optimization algorithms to handle DG allocation, different single-objective, and multi-objective OPF problems. …”
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A discrete simulated kalman filter optimizer for combinatorial optimization problems
Published 2022“…An example of a numerical algorithm is the simulated Kalman filter (SKF). Various method has been introduced as an extension of a numerical algorithm to adapt it to a discrete search space. …”
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Hybrid fuzzy-sliding mode observer design for estimation and advanced control of an ethylene polymerization process / Jarinah Mohd Ali
Published 2017“…Observers are computational algorithms designed to estimate unmeasured state variables due to the lack of appropriate estimating devices or to replace the high-priced sensors in a plant. …”
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