Search Results - (( model validation system algorithm ) OR ( _ identification means algorithm ))
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1
System identification using Extended Kalman Filter
Published 2017“…System identification is getting more intensive from researcher to develop an algorithm with work efficiently and more accurate. …”
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Student Project -
2
MULTIVARIABLE CLOSED-LOOP SYSTEM IDENTIFICATION USING ITERATIVE LEAKY LEAST MEAN SQUARES METHOD
Published 2017“…In this research. novel algorithms have been developed to: (I) isolate the less interacting channe Is using a modified partial correlation algorithm. (2) achieve unbiased and consistent parameter estimates using an iterative LLMS algorithm and (3) develop parsimonious models for closed-loop MIMO systems. …”
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Thesis -
3
Analysis of Toothbrush Rig Parameter Estimation Using Different Model Orders in Real Coded Genetic Algorithm (RCGA)
Published 2024“…System identification is a method to build a model for a dynamic system from the experimental data. …”
Article -
4
Analysis of toothbrush rig parameter estimation using different model orders in Real-Coded Genetic Algorithm (RCGA)
Published 2018“…System identification is a method to build a model for a dynamic system from the experimental data. …”
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Article -
5
Hub Angle Control for A Single Link Flexible Manipulator Based on Cuckoo Search Algorithm
Published 2021“…System identification was implemented via swarm intelligence algorithm known as cuckoo search algorithms based on auto regressive with exogenous model structure. …”
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Proceeding -
6
Widely linear dynamic quaternion valued least mean square algorithm for linear filtering
Published 2017“…A superior performance is achieved by the proposed algorithms in system modeling where the DQLMS was able to track the correct weights values of the different modeled systems 430 sample faster than the QLMS and ZA-QLMS algorithms while the WL-DQLMS was faster than the WLQLMS algorithm by 950 samples. …”
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Thesis -
7
Dynamic modelling of a flexible beam structure using feedforward neural networks for active vibration control
Published 2019“…The performance of modified SFS algorithm to train a nonlinear auto-regressive exogenous model (NARX) structure FNNs-based model of the system was then compared with its predecessor and with several well-known metaheuristic algorithms. …”
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Article -
8
Parametric system identification and active vibration control of vibrational structures using genetic algorithm
Published 2007“…The models were validated using one step ahead (OSA) prediction, mean squared error (MSE) and correlation tests. …”
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Thesis -
9
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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Thesis -
10
Parametric and non-parametric identification of a two dimensional flexible structure
Published 2006“…The parametric approaches obtaining linear parametric models of the system using recursive least squares and genetic algorithms. …”
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Article -
11
ANFIS Identification Model of an Advanced Process Control (APC) Pilot Plant
Published 2010“…Adaptive Network Based Fuzzy Inference System (ANFIS) uses a hybrid computational algorithm for modeling systems. …”
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Conference or Workshop Item -
12
Mayfly Algorithm for Modelling a Horizontal Flexible Plate Structure
Published 2024“…Researchers have devised various approaches to suppress unwanted vibrations, with contemporary studies often employing system identification techniques utilizing swarm intelligence algorithms to construct dynamic models of flexible structures. …”
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Article -
13
Self-calibration algorithm for a pressure sensor with a real-time approach based on an artificial neural network
Published 2018“…To verify the proposed model’s capability to build a self-calibration algorithm, the model was tested using an untrained input data set. …”
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Article -
14
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. …”
Article -
15
Real time self-calibration algorithm of pressure sensor for robotic hand glove system
Published 2019“…The model was tested using an untrained input data set in order to verify the Proposed model’s capability for implementing a self-calibration algorithm. …”
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Thesis -
16
Online system identification development based on recursive weighted least square neural networks of nonlinear hammerstein and wiener models.
Published 2022“…Another method is system identification which is also called experimental modeling. …”
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Thesis -
17
Normalized SPSA for Hammerstein model identification of twin rotor and electro-mechanical positioning systems
Published 2025“…The effectiveness of the proposed method was validated by modeling the actual systems, which included the twin-rotor system (TRS) and the electro-mechanical positioning system (EMPS). …”
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Article -
18
Vibration-based structural damage detection and system identification using wavelet multiresolution analysis / Seyed Alireza Ravanfar
Published 2017“…In addition, the structural parameters of a system can be accurately estimated through the proposed system identification methods for both cases of linear and nonlinear conditions. …”
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Thesis -
19
Fuzzy voice classifier and fuzzy voice pathology identification system
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Working Paper -
20
Automatic detection and indication of pallet-level tagging from rfid readings using machine learning algorithms
Published 2020“…In order to further validate the position of the tagging in the pallet box of the Random Forest model developed, a different predefined location was used to validate the model. …”
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