Search Results - (( parameter optimization techniques algorithm ) OR ( parameter evaluation system algorithm ))
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Two level Differential Evolution algorithms for ARMA parameters estimatio
Published 2013“…The first level searches for the appropriate model order while the second level computes the optimal/sub-optimal corresponding parameters. The performance of the algorithm is evaluated using both simulated ARMA models and practical rotary motion system. …”
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Proceeding Paper -
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Estimation of photovoltaic models using an enhanced Henry gas solubility optimization algorithm with first-order adaptive damping Berndt-Hall-Hall-Hausman method
Published 2024“…A reliable methodology is essential for accurately estimating the parameters of PV models, enabling reliable performance evaluations, effective control studies, accurate analysis of partial shading effects, and optimal optimization of Photovoltaic (PV) systems. …”
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Analysis of toothbrush rig parameter estimation using different model orders in Real-Coded Genetic Algorithm (RCGA)
Published 2018“…In this paper, optimization technique was applied to optimize the objective function that lead to satisfying solution which obtain the dynamic model of the system. …”
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An alternative approach to normal parameter reduction algorithms for decision making using a soft set theory / Sani Danjuma
Published 2017“…Many normal parameter reduction algorithms exist to handle parameter reduction and maintain consistency of decision choices. …”
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Performance Comparison of Particle Swarm Optimization and Gravitational Search Algorithm to the Designed of Controller for Nonlinear System
Published 2014“…This paper presents backstepping controller design for tracking purpose of nonlinear system. Since the performance of the designed controller depends on the value of control parameters, gravitational search algorithm (GSA) and particle swarm optimization(PSO) techniques are used to optimise these parameters in order to achieve a predefined system performance. …”
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Reactive approach for automating exploration and exploitation in ant colony optimization
Published 2016“…Ant colony optimization (ACO) algorithms can be used to solve nondeterministic polynomial hard problems. …”
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Characterization of PV panel and global optimization of its model parameters using genetic algorithm
Published 2023“…This paper details an improved modeling technique for a photovoltaic (PV) module; utilizing the optimization ability of a genetic algorithm, with different parameters of the PV module being computed via this approach. …”
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A Real-Coded Dynamic Genetic Algorithm For Optimizing Driver’s Model In Emission Test Cycle
Published 2015“…This paper proposes a real-coded Genetic Algorithm for finding optimal parameters’ values of a driver’s model. …”
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A new hybrid deep neural networks (DNN) algorithm for Lorenz chaotic system parameter estimation in image encryption
Published 2023“…In addition, the hyperparameter tuning problem is considered in this research to improve the developed hybrid model by using the AOA algorithm. Lastly, a new hybrid technique suggests tackling the current image encryption application problem by using the estimated parameters of chaotic systems with an optimization algorithm, the SKF algorithm. …”
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11
Optimal power flow using a hybridization algorithm of arithmetic optimization and aquila optimizer
Published 2024“…Next, a piecewise linear map is employed to reduce the energy parameter's (E) randomness. To evaluate the performance of the proposed AO-AOA algorithm, it is tested on two well-known power systems i.e., IEEE 30-bus test network, and IEEE 118-bus test system. …”
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A novel chaotic flower pollination algorithm for global maximum power point tracking for photovoltaic system under partial shading conditions
Published 2023“…Global optimization; Photovoltaic cells; Algorithm parameters; Environmental conditions; Environmental phenomena; Global maximum power point tracking; Maximum power point tracking techniques; Optimization algorithms; Photovoltaic systems; Standard versions; Maximum power point trackers…”
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Characterization of PV panel and global optimization of its model parameters using genetic algorithm
Published 2013“…This paper details an improved modeling technique for a photovoltaic (PV) module; utilizing the optimization ability of a genetic algorithm, with different parameters of the PV module being computed via this approach. …”
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Evaluating Bees Algorithm for Sequence-based T-way Testing Test Data Generation
Published 2018“…T-way testing is a testing technique that is used to detect faults due to parameter interactions or software configurations. …”
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Efficient Time-Varying q-Parameter Design for q-Incremental Least Mean Square Algorithm with Noisy Links
Published 2022“…Moreover, for the proposed NL-qILMS, we also devised various time-varying techniques for the selection of the optimal q-parameter to improve the performance. …”
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Comparison of mabsa, PSO and GWO of PI-PD controller for dc motor
Published 2024“…In general, when enhancing the DC motor system, the modified adaptive bats sonar algorithm (MABSA) is an exceptionally effective optimization technique that consistently achieves an optimal outcome.…”
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Data-driven PID controller of wind turbine systems using safe experimentation dynamics algorithm
Published 2024“…SEDA, a single-agent based optimization technique, requires only one function evaluation per iteration, alleviating computational burdens. …”
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Conference or Workshop Item -
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Performance comparison between genetic algorithm and ant colony optimization algorithm for mobile robot path planning in global static environment / Nohaidda Sariff
Published 2011“…The main goal of this research is to compare the performances between Genetic Algorithm (GA) and Ant Colony Optimization (ACO) algorithm. …”
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A hybrid sampling-based path planning algorithm for mobile robot navigation in unknown environments
Published 2013“…Afterward, a genetic algorithm-based optimization framework was designed to improve the interpretability and accuracy of the proposed fuzzy-tabu controller by optimizing the parameters of the FLC and also some of the planner’s parameters in order to improve the quality of the generated paths and runtimes of the planner and also to decrease the variation of the results in different runs of the planner. …”
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