Search Results - (( parameter validation using algorithm ) OR ( simulation optimization method algorithm ))
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Characterization of PV panel and global optimization of its model parameters using genetic algorithm
Published 2023“…The Manufacturer's Data Sheet information is used as a basis for the purpose of parameter optimization, with an average absolute error fitness function formulated; and a numerical iterative method used to solve the voltage-current relation of the PV module. …”
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Optimization of milling parameters using ant colony optimization
Published 2008“…The simulation based on ACO algorithm are successful develop and the optimization of parameters values is to maximize the production rate is obtain from the simulation.…”
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Characterization of PV panel and global optimization of its model parameters using genetic algorithm
Published 2013“…The Manufacturer's Data Sheet information is used as a basis for the purpose of parameter optimization, with an average absolute error fitness function formulated; and a numerical iterative method used to solve the voltage-current relation of the PV module. …”
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Collaborative simulated annealing genetic algorithm for geometric optimization of thermo-electric coolers
Published 2015“…Equality constraint and inequality constraint were taken into consideration. The results of optimization obtained by using CSAGA were validated by comparing with those obtained by using stand-alone genetic algorithm and simulated annealing optimization technique. …”
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Collaborative simulated annealing genetic algorithm for geometric optimization of thermo-electric coolers
Published 2016“…Equality constraint and inequality constraint were taken into consideration. The results of optimization obtained by using CSAGA were validated by comparing with those obtained by using stand-alone genetic algorithm and simulated annealing optimi-zation technique. …”
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Decentralized Intelligent PID based controller tuned by Evolutionary Algorithm for Double Link Flexible Robotic Manipulator with Experimental Validation
Published 2018“…The controllers are incorporated with optimization algorithm that is PSO to find out the parameters of the PID controllers. …”
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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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Impact of evolutionary algorithm on optimization of nonconventional machining process parameters
Published 2025“…Using a Python environment, three evolutionary algorithms such as, Particle Swarm Optimization (PSO), Ant Colony Optimization (ACO), and Firefly Algorithm (FA), were simulated to evaluate their effectiveness in minimizing surface roughness (Ra). …”
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A firefly algorithm based hybrid method for structural topology optimization
Published 2020“…The proposed method was validated using two-dimensional benchmark problems and the results were compared with results using the OC method. …”
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Parameter characterization of PEM fuel cell mathematical models using an orthogonal learning-based GOOSE algorithm
Published 2025“…The orthogonal learning mechanism improves the performance of the original GOOSE algorithm. This FC model uses the root mean squared error as the objective function for optimizing the unknown parameters. …”
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Optimal design of power system stabilizer for multimachine power system using farmland fertility algorithm
Published 2020“…The eigenvalue and phasor simulation analysis results are compared so as to validate the efficiency of both optimization methods for the PSSs design thus, to control low frequency oscillations (LFOs) which improves the system dynamic stability. …”
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Simulation and design of A DC-DC synchronous converter by intelligent optimization techniques
Published 2010“…The derived optimal parameters of the converter from Genetic Algorithm method are compared with those obtained using the other two intelligent techniques.…”
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Load dispatch optimization of open cycle industrial gas turbine plant incorporating operational, maintenance and environmental parameters
Published 2006“…The objective of this work is to develop a multi-objective optimization model and optimization algorithm for load dispatching optimization of open cycle gas turbine plant that not only consider operational parameters, but also incorporates maintenance and environmental parameters. …”
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Optimal overcurrent relay solutions for protection coordination using metaheuristics approaches with penalty function method
Published 2024“…The OCRC is established by manipulating the current known as plus setting (PS) and time delay known as time multiplier setting (TMS) parameters. The optimized value of the TMS and PS will be selected using the algorithms to ensure the minimize result of the objective function. …”
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Optimization of chemotherapy using metaheuristic optimization algorithms / Prakas Gopal Samy
Published 2024“…Stability and bifurcation analyses illuminate the model's responsiveness to varying control parameters. Empirical validation and performance assessment are conducted through rigorous benchmarking simulations on the PlatEMO platform, covering ten algorithms. …”
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Intelligent Optimization Techniques for Optimal Power Flow using Interline Power Flow Controller
Published 2010“…The optimal control parameters are derived to minimize the transmission line losses employing three intelligent optimization techniques, namely Particle Swarm Optimization (PSO), Genetic Algorithm and Simulated Annealing. …”
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Physics-guided deep neural network to characterize non-Newtonian fluid flow for optimal use of energy resources
Published 2021“…The performance of the algorithm is validated with experimental datasets. …”
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Using Spiral Dynamic Algorithm for Maximizing Power Production of Wind Farm
Published 2017“…For simplicity, a single row wind farm model with turbulence interaction between turbines is used to validate the proposed approach. Simulation results demonstrate that the SDA based method produces higher total power production compared to the particle swarm optimization (PSO) and game theoretic (GT) based approaches. …”
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