Search Results - (( model estimation method algorithm ) OR ( swarm identification based algorithm ))*
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1
Simultaneous Computation of Model Order and Parameter Estimation for Arx Model Based on Multiswarm Particle Swarm Optimization
Published 2015“…Simultaneous Model Order and Parameter Estimation (SMOPE) is a method of utilizing meta-heuristic algorithm to iteratively determine an optimal model order and parameters simultaneously for an unknown system. …”
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2
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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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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PSO and Linear LS for parameter estimation of NARMAX/NARMA/NARX models for non-linear data / Siti Muniroh Abdullah
Published 2017“…PSO is a swarm-based search algorithm perform a stochastic search to explore the search space. …”
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Nonlinear auto-regressive model structure selection using binary particle swarm optimization algorithm / Ahmad Ihsan Mohd Yassin
Published 2014“…The suboptimal selection of regressor terms leads to models that are non-parsimonious in nature. This thesis proposes the application of a stochastic optimization algorithm called Binary Particle Swarm Optimization algorithm for structure selection of polynomial NARX/NARMA/NARMAX models. …”
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SLOW DRIFT MOTIONS IDENTIFICATION OF FLOATING STRUCTURES USING TIME-VARYING INPUT -OUTPUT MODELS
Published 2015“…Three steps of improvements had been made to increase the modeling capacity of input-output models. The first step is presenting the backward estimator and combined forward-backward estimator instead of the only forward estimator in the original input-output models; the second step is reformulating the input-output models into a state-space model so that the Kalman Smoother (KS) adaptive filter can be used to estimate the model 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) to form the PSO-KS, GA-KS and ABC-KS as estimation methods.…”
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7
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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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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Parameter identification of thermoelectric modules using enhanced slime mould algorithm (ESMA)
Published 2024“…Acquired results which demonstrate lower values of RMSE and parameter deviation index against the standard SMA and other preceding algorithms such as particle swarm optimization, sine cosine algorithm, moth flame optimizer and ant lion optimizer ultimately verified ESMA’s efficacy as an effective approach for accurate model identification.…”
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Optimal parameter estimation of permanent magnet synchronous motor by using Mothflame optimization algorithm / Abdolmajid Dejamkhooy and Sajjad Asefi
Published 2018“…Simulation results and their comparison with Particle Swarm Optimization based method show high performance and good ability of the proposed method in PMSM parameter estimation.…”
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System identification of essential oil extraction system using non-linear autoregressive model with exogenous inputs (NARX) / Farahida Awadz
Published 2010“…The tests that been performed based on the essential oil extraction system by (Rahiman, 2009), show that the BPSO has the potential to become an effective method to determine the NARX model structure in the system identification model.…”
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12
Towards enhanced remaining useful life prediction of lithium-ion batteries with uncertainty using optimized deep learning algorithm
Published 2025“…In addition, to validate the prediction performance of the proposed LSA + LSTM model, extensive comparisons are performed with other popular optimization-based deep learning methods including artificial bee colony (ABC) based LSTM (ABC + LSTM), gravitational search algorithm (GSA) based LSTM (GSA + LSTM), and particle swarm optimization (PSO) based LSTM (PSO + LSTM) model using different error matrices. …”
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Improved genetic algorithm for direct current motor high speed controller implemented on field programmable gate array
Published 2019“…There are many researches have been done to optimize PI controller based evolutionary algorithm, such as Genetic Algorithm (GA). …”
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14
Simultaneous computation of model order and parameter estimation for ARX model based on single swarm and multi swarm simulated Kalman filter
Published 2017“…The performance of SMOPE and SMOPE-MS has been examined through the utilization of Particle Swarm Optimization (PSO) and Gravitational Search Algorithm (GSA). …”
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Control of grain drying process using self-tuning quantitative feedback theory
Published 2011“…The robust QFT-based controller was designed based on the obtained grain dryer process model. …”
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Improving particle swarm optimization via adaptive switching asynchronous – synchronous update
Published 2018“…Particle swarm optimization (PSO) is a population-based metaheuristic optimization algorithm that solves a problem through iterative operations. …”
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Indexed Article -
18
Identification of transformer fault based on dissolved gas analysis using hybrid support vector machine-modified evolutionary particle swarm optimisation
Published 2018“…In this work, a hybrid support vector machine (SVM) with modified evolutionary particle swarm optimisation (EPSO) algorithm was proposed to determine the transformer fault type. …”
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Improving particle swarm optimization via adaptive switching asynchronous – synchronous update
Published 2018“…Particle swarm optimization (PSO) is a population-based metaheuristic optimization algorithm that solves a problem through iterative operations. …”
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NARX modelling for steam distillation pilot plant using binary particle swarm optimisation technique / Najidah Hambali
Published 2019“…This study proposes a system identification of SDPP using NARX model. The model structure selection of polynomial NARX had been focused on Binary Particle Swarm Optimisation (BPSO) algorithm. …”
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