Search Results - (( simulation optimization using algorithm ) OR ( using identification _ algorithm ))
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Opposition- based simulated kalman filters and their application in system identification
Published 2017“…Among the various kinds of optimization algorithms, Simulated Kalman Filter (SKF) is a new population-based optimization algorithm inspired by the estimation capability of Kalman Filter. …”
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Effect of parameters variation on the performance of particle swarm optimization algorithm for tag coverage problem of radio frequency identification network
Published 2016“…In this paper, PSO (Particle Swarm Optimization) algorithm is used to optimize the tag coverage problem. …”
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System identification using Extended Kalman Filter
Published 2017“…All the coding simulation and the results analyzed was done using Matlab programming software.…”
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Comparison between multi-objective and single-objective optimization for the modeling of dynamic systems
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Optimum grouping in a modified genetic algorithm for discrete-time, non-linear system identification
Published 2007“…The genetic algorithm approach is widely recognized as an effective and flexible optimization method for system identification. …”
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Optimum grouping in a modified genetic algorithm for discrete-time, non-linear system identification
Published 2007“…he genetic algorithm approach is widely recognized as an effective and flexible optimization method for system identification. …”
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Optimization of drilling path using the bees algorithm
Published 2021“…In addition to results comparison with other algorithms, the results obtained are verified with simulation results using MasterCAM software. …”
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Optimum grouping in a modified genetic algorithm for discrete-time, non-linear system identification
Published 2007“…The genetic algorithm approach is widely recognized as an effective and flexible optimization method for system identification. …”
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Deterministic Mutation-Based Algorithm for Model Structure Selection in Discrete-Time System Identification
Published 2011“…A deterministic mutation-based algorithm is introduced to overcome this problem. Identification studies using NARX (Nonlinear AutoRegressive with eXogenous input) models employing simulated systems and real plant data are used to demonstrate that the algorithm is able to detect significant variables and terms faster and to select a simpler model structure than other well-known EC methods.…”
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Simultaneous computation of model order and parameter estimation for system identification based on opposition-based simulated Kalman filter
Published 2018“…Simultaneous Model Order and Parameter Estimation (SMOPE) has been proposed to address system identification problem efficiently using optimization algorithms. …”
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Optimization of supply chain management by simulation based RFID with XBEE Network
Published 2015“…In order to solve this problem, a simulation based “Multi-Colony Global Particle Swarm Optimization (MC-GPSO)” algorithm was developed. …”
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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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A novel single parent mating technique in genetic algorithm for discrete - time system identification
Published 2024“…As a popular search method, genetic algorithm (GA) is used for selecting a model structure. …”
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Simulated real-time controller for tuning algorithm using modified hill climbing approach
Published 2014“…Although all adaptive control tuning methodologies depend partially or completely on online plant system identification, the proposed method uses only the model that is used to design the original controller, leading to simplified calculations that require neither high processing power nor long processing time, as opposed to identification techniques calculations. …”
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Autoreclosure in Extra High Voltage Lines using Taguchi’s Method and Optimized Neural Networks
Published 2008“…The algorithms are developed using MATLABTM software. A range of faults are simulated on EHV modeled transmission line using SimPowerSytemsTM, and the spectra of the fault data are analyzed using fast Fourier transform which facilitates extraction of distinct features of each type of fault. …”
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Autoreclosure in Extra High Voltage Lines using Taguchi's Method and Optimized Neural Networks
Published 2009“…The algorithms are developed using MATLAB software. A range of faults are simulated on EHV modeled transmission line using SimPowerSytems, and the spectra of the fault data are analyzed using fast Fourier transform to extract features of each type of fault. …”
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Simulated Kalman Filter with modified measurement, substitution mutation and hamming distance calculation for solving traveling salesman problem
Published 2022“…As a multi-agent algorithm, every agent in the population acts as a Kalman filter by using a standard Kalman filter framework, which includes a simulated measurement process and a best-so-far solution as a reference. …”
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OPTIMIZATION OF HYBRID-FUZZY CONTROLLER FOR SERVOMOTOR CONTROL USING A MODIFIED GENETIC ALGORITHM
Published 2011“…The servomotor's transfer function is obtained via system identification and is modelled using MATLAB commands. …”
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