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Nonlinear auto-regressive model structure selection using binary particle swarm optimization algorithm / Ahmad Ihsan Mohd Yassin
Published 2014“…System Identification (SI) is a control engineering discipline concerned with the discovery of mathematical models based on dynamic measurements collected from the system. …”
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Implementation of Evolutionary Algorithms to Parametric Identification of Gradient Flexible Plate Structure
Published 2023“…This input-output data was then applied in a system identification method, which used an evolutionary algorithm with a linear autoregressive with exogenous (ARX) model structure to generate a dynamic model of the system. …”
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Implementation of Evolutionary Algorithms to Parametric Identification of Gradient Flexible Plate Structure
Published 2023“…This input-output data was then applied in a system identification method, which used an evolutionary algorithm with a linear autoregressive with exogenous (ARX) model structure to generate a dynamic model of the system. …”
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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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Time-varying water temperature modelling of steam distillation pilot plant using NARX-based binary particle swarm optimisation structure selection / Najidah Hambali … [et al.]
Published 2017“…Many studies in current years has concentrated on both linear and nonlinear modelling in the real nonlinear system applications. This study reports a nonlinear modelling for a time-varying process of water temperature by utilising a Binary Particle Swarm Optimisation (BPSO) algorithm based on Nonlinear Auto-Regressive with eXogenous input (NARX) structure. …”
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Identification of continuous-time hammerstein model using improved archimedes optimization algorithm
Published 2024“…The process was evaluated using a numerical example and two practical experiments [twin-rotor system (TRS) and electro-mechanical positioning system (EMPS)]. …”
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Particle swarm optimization with deep learning for human action recognition
Published 2021“…Finally, a deep learning neural network is used to evaluate the methodâ��s effectiveness. …”
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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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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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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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Optimized fuzzy logic sliding mode control with proportional-integral-derivative for an electrohydraulic actuator system
Published 2023“…A particle swarm optimization (PSO) algorithm was implemented as the FLSMC design involves a complicated procedure and mathematical formulations to obtain the optimal value of the designed control variables. …”
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Simultaneous computation of model order and parameter estimation for ARX model based on single swarm and multi swarm simulated Kalman filter
Published 2017“…The objective of this paper is to test the effectiveness of SKF in solving system identification problem throughout SMOPE and SMOPE-MS. …”
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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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Particle swarm modelling of a flexible beam structure
Published 2009“…In this study, system identification scheme based on PSO is formulated to obtain a dynamic model of the beam in parametric form. …”
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Proceeding Paper -
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Neuro-modelling and fuzzy logic control of a two-wheeled wheelchair system
Published 2024“…A neural network-based Nonlinear Autoregressive model with Exogenous Inputs (NARX) was developed, capturing and behaving similar to the complex dynamics of the wheelchair system with the identification on the experimental input–output data. …”
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Parametric modelling of a TRMS using dynamic spread factor particle swarm optimisation
Published 2009“…Particle swarm optimization (PSO) is demonstrated as an efficient global search method for nonlinear complex systems without any a priory knowledge of the system structure. …”
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Proceeding Paper -
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Simultaneous Computation of Model Order and Parameter Estimation for Arx Model Based on Multiswarm Particle Swarm Optimization
Published 2015“…Experiments are performed on six system identification problems. The obtained results prove that incorporating the multi-swarm approach is a good idea to improve original SMOPE.…”
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System identification of essential oil extraction system using non-linear autoregressive model with exogenous inputs (NARX) / Farahida Awadz
Published 2010“…This project explores the application of system identification using Non-Linear Autoregressive Model with Exogeneous Inputs (NARX) of an essential oil extraction system. …”
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