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  1. 1
    System identification using Extended Kalman Filter

    System identification using Extended Kalman Filter by Alias, Ahmad Hafizi

    Published 2017
    “…In order to evaluate the performance of the EKF learning algorithm, the proposed algorithm validation were analyzed using model validation methods as a checker such as One Step Ahead (OSA) and correlation coefficient (R2). …”
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  2. 2
    Analysis of Toothbrush Rig Parameter Estimation Using Different Model Orders in Real Coded Genetic Algorithm (RCGA)

    Analysis of Toothbrush Rig Parameter Estimation Using Different Model Orders in Real Coded Genetic Algorithm (RCGA) by Ainul, H. M. Y., Salleh, S. M., Halib, N., Taib, H., Fathi, M. S.

    Published 2024
    “…System identification is a method to build a model for a dynamic system from the experimental data. …”
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  3. 3
    Optimum grouping in a modified genetic algorithm for discrete-time, non-linear system identification

    Optimum grouping in a modified genetic algorithm for discrete-time, non-linear system identification by Jamaluddin, H., Samad, M. F. A., Ahmad, R., Yaacob, M. S.

    Published 2007
    “…he genetic algorithm approach is widely recognized as an effective and flexible optimization method for system identification. …”
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  4. 4
    Optimum grouping in a modified genetic algorithm for discrete-time, non-linear system identification

    Optimum grouping in a modified genetic algorithm for discrete-time, non-linear system identification by Jamaluddin, Hishamuddin, Abd. Samad, M. F., Ahmad, Robiah, Yaacob, M. S.

    Published 2007
    “…The genetic algorithm approach is widely recognized as an effective and flexible optimization method for system identification. …”
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  5. 5
    MULTIVARIABLE CLOSED-LOOP SYSTEM IDENTIFICATION USING ITERATIVE LEAKY LEAST MEAN SQUARES METHOD

    MULTIVARIABLE CLOSED-LOOP SYSTEM IDENTIFICATION USING ITERATIVE LEAKY LEAST MEAN SQUARES METHOD by MOHAMED OSMAN, MOHAMED ABDELRAHIM

    Published 2017
    “…All the proposed algorithms are demonstrated with the help of extensive simulation case studies and a real pilot-scale distillation column with appropriate validation procedures.…”
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    Thesis
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  6. 6
    Simultaneous Computation of Model Order and Parameter Estimation for System Identification Based on Gravitational Search Algorithm

    Simultaneous Computation of Model Order and Parameter Estimation for System Identification Based on Gravitational Search Algorithm by Kamil Zakwan, Mohd Azmi, Pebrianti, Dwi, Zuwairie, Ibrahim, Shahdan, Sudin, Sophan Wahyudi, Nawawi

    Published 2015
    “…System identification is a technique used to obtain a mathematical model of a system by performing analysis of input-output characteristic of the system. …”
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  7. 7
    Sketch-based 3D modeling of symmetric objects from wireframe sketches on paper

    Sketch-based 3D modeling of symmetric objects from wireframe sketches on paper by Yahya, Zahrah

    Published 2016
    “…The results of the validation show a complete similarity between each original face and the output from our algorithm. …”
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    Thesis
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  8. 8
    Effects of user selected conditions on modeling of dynamic systems using adaptive fuzzy model

    Effects of user selected conditions on modeling of dynamic systems using adaptive fuzzy model by Yaacob, Mohd. Shafiek, Jamaluddin, Hishamuddin

    Published 2001
    “…In this paper, major properties of an adaptive fuzzy model as a system identifier when trained by the back-propagation algorithm are discussed. …”
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  9. 9
    Analysis of toothbrush rig parameter estimation using different model orders in Real-Coded Genetic Algorithm (RCGA)

    Analysis of toothbrush rig parameter estimation using different model orders in Real-Coded Genetic Algorithm (RCGA) by Ainul, H. M. Y., Salleh, S. M., Halib, N., Taib, H., Fathi, M. S.

    Published 2018
    “…System identification is a method to build a model for a dynamic system from the experimental data. …”
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    Article
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  10. 10
    Optimum grouping in a modified genetic algorithm for discrete-time, non-linear system identification

    Optimum grouping in a modified genetic algorithm for discrete-time, non-linear system identification by Abd Samad, Md Fahmi

    Published 2007
    “…The genetic algorithm approach is widely recognized as an effective and flexible optimization method for system identification. …”
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  11. 11
    Single parent mating in genetic algorithm for real robotic system identification

    Single parent mating in genetic algorithm for real robotic system identification by Abd Samad, Md Fahmi, Zainuddin, Farah Ayiesya

    Published 2023
    “…As a popular search method, genetic algorithm (GA) is used for selecting a model structure. …”
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  12. 12
    Musical instrument identification using Convolutional Neural Network (CNN) algorithm / Muhammad Nur Azri Irfan Abdul Rahman

    Musical instrument identification using Convolutional Neural Network (CNN) algorithm / Muhammad Nur Azri Irfan Abdul Rahman by Abdul Rahman, Muhammad Nur Azri Irfan

    Published 2025
    “…The motivation behind the project was to help automate the cumbersome task of validating instruments from images using Convolutional Neural Network (CNNs) algorithm to identify the musical instrument so that this task could be completed with higher accuracy. …”
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  13. 13
    Dynamic modelling of a flexible beam structure using feedforward neural networks for active vibration control

    Dynamic modelling of a flexible beam structure using feedforward neural networks for active vibration control by Tuan Abdul Rahman, Tuan Ahmad Zahidi, As'arry, Azizan, Abdul Jalil, Nawal Aswan, Raja Ahmad, Raja Mohd Kamil

    Published 2019
    “…Correlation tests were used to validate the obtained model. Based on the proposed method, a small mean squared error value has been achieved in the validation phase. …”
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  14. 14
    SYSTEM IDENTIFICATION AND MODEL PREDICTIVE CONTROL FOR INTERACTING SERIES PROCESS WITH NONLINEAR DYNAMICS

    SYSTEM IDENTIFICATION AND MODEL PREDICTIVE CONTROL FOR INTERACTING SERIES PROCESS WITH NONLINEAR DYNAMICS by SETYO WIBOWO, TRI CHANDRA

    Published 2009
    “…The subspace system identification method is used to estimate the linear model parameters. …”
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  15. 15
    Autoreclosure in Extra High Voltage Lines using Taguchi's Method and Optimized Neural Networks

    Autoreclosure in Extra High Voltage Lines using Taguchi's Method and Optimized Neural Networks by Desta, Zahlay F., K.S., Rama Rao

    Published 2009
    “…The fault identification prior to reclosing is based on optimized artificial neural network associated with standard Error Back-Propagation, Levenberg Marquardt Algorithm and Resilient Back-Propagation training algorithms together with Taguchi’s Method. …”
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  16. 16
    Autoreclosure in Extra High Voltage Lines using Taguchi’s Method and Optimized Neural Networks

    Autoreclosure in Extra High Voltage Lines using Taguchi’s Method and Optimized Neural Networks by Desta, Zahlay F., K.S., Ramarao, Taj, Mohammed Baloch

    Published 2008
    “…The fault identification prior to reclosing is based on optimized artificial neural network associated with standard Error Back-Propagation, Levenberg Marquardt Algorithm and Resilient Back-Propagation training algorithms together with Taguchi’s Method. …”
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  17. 17
    Self-tuning control of an electro-hydraulic actuator system

    Self-tuning control of an electro-hydraulic actuator system by Ghazali, Rozaimi, Md Sam, Yahaya, Rahmat, Mohd Fua'ad, Jusoff, Kamaruzaman, Zulfatman, Mohd Hashim, Abd Wahab Ishari

    Published 2011
    “…A discrete-time model is developed using system identification method to represent the EHA system and residual analysis is used for model validation. …”
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  18. 18
    Segment Particle Swarm Optimization Adoption for Large-Scale Kinetic Parameter Identification of Metabolic Network Model

    Segment Particle Swarm Optimization Adoption for Large-Scale Kinetic Parameter Identification of Metabolic Network Model by Azrag, M. A. K., Tuty Asmawaty, Abdul Kadir, Jaber, Aqeel S.

    Published 2018
    “…The seven sensitive kinetic parameters were used in both the algorithms to minimize the model response errors. The validation results proved the effectiveness of both the proposed methods, which identified the kinetics and minimized the model response errors perfectly.…”
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  19. 19
    Parametric system identification and active vibration control of vibrational structures using genetic algorithm

    Parametric system identification and active vibration control of vibrational structures using genetic algorithm by Mohammad Sofi @ Aziz, Azfi Zaihan

    Published 2007
    “…The models were validated using one step ahead (OSA) prediction, mean squared error (MSE) and correlation tests. …”
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  20. 20
    A graphical user interface application for continuous-time identification of dynamical system

    A graphical user interface application for continuous-time identification of dynamical system by Rahmat, Mohd. Fua'ad, Omar, Rosli, Jamaluddin, Hishamuddin

    Published 2002
    “…This paper introduces a Graphical User Interface (GUI) application in system identification and parameter estimation of dynamic systems using Generalized Poisson Moment Functionals (GPMF) method based on Instrumental Variable (IV) algorithm. …”
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