Search Results - (( parameters deviations methods algorithm ) OR ( parameter simulation based algorithm ))
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1
Parameter estimation and outlier detection in linear functional relationship model / Adilah Abdul Ghapor
Published 2017“…The simulation results indicate that the proposed method is suitable to detect a single outlier. …”
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2
PID Parameters Improvement for AGC in Three Parallel-Connected Power Systems
Published 2016“…The optimal parameters of the PID scheme optimized by the proposed MS algorithm are compared with that one’s obtained by GA algorithm, and the proposed method has proven that its performance is more efficient and improved as well. …”
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3
Neural Network Model and Finite Element Simulation of Spring back in Plane-Strain Metallic Beam Bending
Published 2006“…The standard deviation between the finite element method and the neural network metamodels for the two functions are 0.635 degree and 0.985 mm respectively. …”
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4
Investigation of firefly algorithm and chaos firefly algorithm for load prequency control / Zaid Najid
Published 2015“…In order to obtain the best controller parameter values for LFC, Firefly Algorithm (FA) and Chaos Firefly Algorithm (CFA) are used. …”
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5
Impact of evolutionary algorithm on optimization of nonconventional machining process parameters
Published 2025“…These findings indicate that the PSO algorithm excels in delivering superior results while showcasing rapid convergence, robustness, and consistent repeatability in optimizing laser beam machining parameters.…”
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6
Novel farmland fertility algorithm based PIDPSS design for SMIB angular stability enhancement
Published 2020“…A new metaheuristics method called Farmland Fertility Algorithm (FFA) inspired by nature is proposed for optimal design of PIDPSS using a robust ISTSE objective function which had to be minimized. …”
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Comparative study of clustering-based outliers detection methods in circular-circular regression model
Published 2021“…Thus, it has been found that Satari’s algorithm (S-SL algorithm) performs well for any values of sample size n and error concentration parameter. …”
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Comparative study of clustering-based outliers detection methods in circularcircular regression model
Published 2021“…Thus, it has been found that Satari’s algorithm (S-SL algorithm) performs well for any values of sample size n and error concentration parameter. …”
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Comparative study of clustering-based outliers detection methods in circular-circular regression model
Published 2021“…Thus, it has been found that Satari's algorithm (S-SL algorithm) performs well for any values of sample size n and error concentration parameter. …”
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10
Dynamic Robust Bootstrap Algorithm for Linear Model Selection Using Least Trimmed Squares
Published 2009“…They used the classical bootstrap method to estimate the bootstrap location and the scale parameters based on calculating the Mean of Squared Residual (MSR). …”
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11
Parameter estimation and outlier detection for some types of circular model / Siti Zanariah binti Satari
Published 2015“…In this study, we propose an alternative method of constructing a confidence interval based from the distribution of the estimated value of error concentration parameter obtained from the Fisher information matrix. …”
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12
Tuning of PID controller for a synchronous machine connected to a non-linear load
Published 2023“…A PSO algorithm has been proposed to tune the parameters of the PID controller. …”
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13
The multiple outliers detection for circular univariate data using different agglomerative clustering algorithms
Published 2024“…In univariate circular data, the presence of outliers is acclaimed will affect the parameter estimates and inferences. This study proposes the procedure of detecting multiple outliers, particularly for univariate circular data based on agglomerative clustering algorithms. …”
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14
Power system stabilizer optimization using BBO algorithm for a better damping of rotor oscillations owing to small disturbances
Published 2023“…We introduce here a latest biogeography-based optimization (BBO) algorithm to adjust PSS parameters for different operating conditions in order to improve the stability margin and the system damping. …”
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15
Data driven neuroendocrine pid controller for mimo plants based adaptive safe experimentation dynamics algorithm
Published 2020“…The existing data-driven neuroendocrine-PID (NEPID) utilizes the simultaneous perturbation stochastic approximation (SPSA) algorithm as the data-driven tool. However, this SPSA-based method is unable to find the optimal value of the design parameter due to unstable convergence obtained that degrades the controller performance in MIMO systems. …”
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16
Penalized LAD-SCAD estimator based on robust wrapped correlation screening method for high dimensional models
Published 2021“…The SIS method uses the rank correlation screening (RCS) algorithm in the pre-screening step and the traditional Pathwise coordinate descent algorithm for computing the sequence of the regularization parameters in the post screening step for onward model selection. …”
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17
Fault detection and diagnosis using rule-based support system on fatty acid fractionation column
Published 2003“…Process variables are defined as fault if they are deviated outside this region. Identification of causes, consequences and suggested actions for each deviation assisted by Hazard and Operability Study (HAZOP) analysis are generated into rule-based algorithm. …”
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18
Sensorless Adaptive Fuzzy Logic Control Of Permanent Magnet Synchronous Motor
Published 2008“…Both experimental and simulation results obtained from the HMRASC and the position angle estimation algorithms showed superior results compared to other methods presented in the literature.…”
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19
Firefly analytical hierarchy algorithm for optimal allocation and sizing of distributed generation in radial distribution network
Published 2022“…The results showed that the Firefly Algorithm (FA) performs much better for the optimal allocation and sizing of DG compared to the other metaheuristic techniques, particularly based on convergence characteristics and standard deviation. …”
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20
Analysis of robot localisation performance based on extended kalman filter
Published 2015“…First is the performance of the algorithm using different parameters in which different velocities and number of landmarks have been used to determine the accuracy of the localisation method. …”
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