Search Results - (( simulation optimization method algorithm ) OR ( parameter adaptation method 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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BBO algorithm-based tuning of PID controller for speed control of synchronous machine
Published 2023Article -
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Comparative analysis of spiral dynamic algorithm and artificial bee colony optimization for position control of flexible link manipulators
Published 2024“…Overall, the simulation results indicate that employing these algorithms for PID parameter optimization effectively enhances the manipulator's transient response and minimizes steady-state error, offering promising implications for real-world robotic applications.…”
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Parameter characterization of PEM fuel cell mathematical models using an orthogonal learning-based GOOSE algorithm
Published 2025“…This approach demonstrates the ability of the GOOSE algorithm to simulate complex systems and enhances the robustness and adaptability of the simulation tool by integrating essential behaviours into the computational framework. …”
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Recent Evolutionary Algorithm Variants for Combinatorial Optimization Problem
Published 2023“…Hybridization in evolutionary algorithm mechanisms such as initialization methods, local searches, specific design operators, and self-adaptive parameters enhance the algorithm’s performance. …”
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A Method For Solving Mult-Objective Optimization Problem: Vector Evaluated Genetic Algorithm (Vega)
Published 2009“…However, it is impractical to solve MOOP by using classical methods due to its complexity. Genetic Algorithms (GAs) are a powerful stochastic search in solving optimization problems. …”
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Adaptive differential evolution algorithm with fitness based selection of parameters and mutation strategies / Rawaa Dawoud Hassan Al-Dabbagh
Published 2015“…The second taxonomy is a new taxonomy proposed to classify the adaptive DE algorithms in particular into two categories (DE with adaptive parameters and DE with adaptive parameters and strategies) considering the adaptive components used in this algorithm. …”
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Simulated real-time controller for tuning algorithm using modified hill climbing approach
Published 2014“…Often, it is necessary to calibrate a certain parameters of a control system due to plant parameters fluctuation over time.In this research, an intelligent algorithmic tuning technique suitable for realtime system tuning based on hill climbing optimization algorithm and model reference adaptive control system (MRAC) technique is proposed. …”
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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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Efficiency improvement of a standalone photovoltaic system using fuzzy-based maximum power point tracking algorithm
Published 2016“…MPPT algorithms can be categorized into classical methods and artificial intelligence-based methods. …”
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Fair bandwidth distribution marking and scheduling algorithm in network traffic classification
Published 2019“…Finally, propose a new method of obtaining optimal parameters dropping functions for Random Early Detection (RED) algorithm. …”
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Single Machine Connected Infinite Bus system tuning coordination control using biogeography-based optimization algorithm
Published 2023“…The BBO algorithm is demonstrated to tune the control parameter values of coordinated damping controller. …”
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Data driven neuroendocrine pid controller for mimo plants based adaptive safe experimentation dynamics algorithm
Published 2020“…Data-driven tools are an optimization method to find the optimal controller parameters using the system’s input and output data. …”
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Performance Enhancement of Routing Protocols in Mobile Wireless Ad-Hoc Networks Using Fuzzy Reasoning Algorithm
Published 2006“…Because it it often impossible to know what enviroment the protocol will find itself in, and because the enviroment can change unpredictably, the routing protocol must be able to adapt automatically. In this thesis, we use a fuzzy reasoning algorithm (FRA) as a highly adaptive algorithm to achieve that goal. …”
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Modeling the powder compaction process using the finite element method and inverse optimization
Published 2011“…This paper focuses on studying and adapting modeling techniques using the finite element method to simulate the rigid die compaction of metal powders. …”
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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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Distributed joint power control, beamforming and spectrum leasing for cognitive two-way relay networks
Published 2017“…A search method with numerous advantages over conventional algorithms, has been designed to solve the optimization problems with an enhanced global optimality and convergence speed. …”
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Comparison of mabsa, PSO and GWO of PI-PD controller for dc motor
Published 2024“…The swarm intelligence group selected Particle Swarm Optimization (PSO), Grey Wolf Optimization (GWO), and Modified Adaptive Bats Sonar Algorithms (MABSA) to optimize the parameters of the PI-PD controller. …”
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