Search Results - (( using optimization methods algorithm ) OR ( parameters identification method algorithm ))
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1
A hybrid metaheuristic algorithm for identification of continuous-time Hammerstein systems
Published 2021“…The proposed hybrid method also achieved better performance in modeling of the twin-rotor system as well as the flexible manipulator system and provided better solutions compared to other optimization methods including Particle Swarm Optimizer, Grey Wolf Optimizer, Multi-Verse Optimizer and Sine Cosine Algorithm.…”
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2
Identification of continuous-time model of hammerstein system using modified multi-verse optimizer
Published 2021“…The mMVO based method is then used for identifying the parameters of linear and nonlinear subsystems in the Hammerstein model using the given input and output data. …”
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3
Parameter identification of thermoelectric modules using enhanced slime mould algorithm (ESMA)
Published 2024“…The proposed method incorporates a pair of modifications to the standard slime mould algorithm (SMA). …”
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4
Modified multi-verse optimizer for nonlinear system identification of a double pendulum overhead crane
Published 2021“…The efficiency of the proposed HMVOSCA algorithm is evaluated using the convergence curve, parameter estimation error, bode plot, function plot, and Wilcoxon's test method. …”
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5
Identification of the thermoelectric cooler using hybrid multi-verse optimizer and sine cosine algorithm based continuous-time Hammerstein model
Published 2021“…This paper presents the identification of the ThermoElectric Cooler (TEC) plant using a hybrid method of Multi-Verse Optimizer with Sine Cosine Algorithm (hMVOSCA) based on continuous-time Hammerstein model. …”
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6
Hybrid intelligent methods for parameter identification and load frequency control in power system
Published 2014“…For example, the classical methods for parameter identification (LSE and MLE), the classical methods for LFC (PI, PD and PID) and the intelligent methods (fuzzy logic, neural network, genetic algorithm, and PSO). …”
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Optimal parameter estimation of permanent magnet synchronous motor by using Mothflame optimization algorithm / Abdolmajid Dejamkhooy and Sajjad Asefi
Published 2018“…In the next step, the parameter identification as an optimization problem is solved by Moth-flame optimization, which is a novel nature-inspired heuristic algorithm. …”
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8
Analysis of Toothbrush Rig Parameter Estimation Using Different Model Orders in Real Coded Genetic Algorithm (RCGA)
Published 2024“…Real-coded genetic algorithm (RCGA) as a stochastic global search method was applied for optimization. …”
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Analysis of toothbrush rig parameter estimation using different model orders in Real-Coded Genetic Algorithm (RCGA)
Published 2018“…Realcoded genetic algorithm (RCGA) as a stochastic global search method was applied for optimization. …”
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10
Mixed Unscented Kalman Filter and differential evolution for parameter identification
Published 2013“…DE algorithm is integrated into the UKF algorithm to optimize the Kalman gain obtained. …”
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11
Improved intrusion detection algorithm based on TLBO and GA algorithms
Published 2021“…Optimization algorithms are widely used for the identification of intrusion. …”
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12
Identification of manipulator kinematics parameters through iterative method
“…A gradient projection algorithm was used to obtain the optimal parameters that had satisfied the world coordinates from the joint angles reading. …”
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13
Particle swarm optimization for NARX structure selection application on DC motor model: article / Mohd I. Abdullah
“…This paper presents the nonlinear identification of a DC motor using Binary Particle Swarm Optimization (BPSO) algorithm, as a model structure selection method, replacing the typical Orthogonal Least Squares (OLS) used in system identification. …”
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Particle swarm optimization for NARX structure selection: application on DC motor model / Mohd Ikhwan Abdullah
Published 2010“…This thesis was presents the nonlinear identification of a DC motor using Binary Particle Swarm Optimization (BPSO) algorithm, as a model structure selection method, replacing the typical Orthogonal Least Squares (OLS) used in system identification. …”
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15
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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16
Segment Particle Swarm Optimization Adoption for Large-Scale Kinetic Parameter Identification of Metabolic Network Model
Published 2018“…However, this paper focuses on adopting segment particle swarm optimization (PSO) and PSO algorithms for large-scale kinetic parameters identification. …”
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Tree-based contrast subspace mining method
Published 2020“…Hence, this thesis presents the optimization of parameters values for the tree-based method by genetic algorithm. …”
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Taguchi's method for optimized neural network based autoreclosure in extra high voltage lines
Published 2008“…The fault identification prior to reclosing is based on optimized artificial neural network associated with Levenberg Marquardt algorithm to train the ANN and Taguchi's Method to find optimal parameters of the algorithm and number of hidden neurons. …”
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19
Nonlinear auto-regressive model structure selection using binary particle swarm optimization algorithm / Ahmad Ihsan Mohd Yassin
Published 2014“…A MySQL database was created to analyze the optimization results and speed up computations of the optimization algorithm. …”
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20
Single parent mating in genetic algorithm for real robotic system identification
Published 2023“…A typical rule is that the final model must have a good balance between parsimony and accuracy. As a popular search method, genetic algorithm (GA) is used for selecting a model structure. …”
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