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  1. 1
    Development of auto-tracking mobile robot

    Development of auto-tracking mobile robot by Ahmad Shahrizan, Abdul Ghani, Suresh, Sundarajoo

    Published 2018
    “…In order to improve the accuracy of identification of object in different illumination and background conditions, the implementation of HSI color model is used in image processing algorithm. …”
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  2. 2
    Nonlinear auto-regressive model structure selection using binary particle swarm optimization algorithm / Ahmad Ihsan Mohd Yassin

    Nonlinear auto-regressive model structure selection using binary particle swarm optimization algorithm / Ahmad Ihsan Mohd Yassin by Mohd Yassin, Ahmad Ihsan

    Published 2014
    “…The identification process of NARX/NARMA/NARMAX involves structure selection and parameter estimation, which can be simultaneously performed using the widely accepted Orthogonal Least Squares (OLS) algorithm.…”
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  3. 3
    Improvement of Auto-Tracking Mobile Robot based on HSI Color Model

    Improvement of Auto-Tracking Mobile Robot based on HSI Color Model by Sundarajoo, Suresh, Ahmad Shahrizan, Abdul Ghani

    Published 2018
    “…In order to improve the accuracy of identification of object in different illumination and background conditions, the implementation of HSI color model is used in image processing algorithm. …”
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  4. 4
    Implementation of Frequency Drift for Identification of Solar Radio Burst Type II

    Implementation of Frequency Drift for Identification of Solar Radio Burst Type II by Roslan, Umar, Nur Zulaikha, Mohd Afandi, Zamri, Zainal Abidin

    Published 2016
    “…The value of frequency drift was used as the main idea in this auto classify algorithm because it can easily implemented using MATLAB. …”
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  5. 5
    The Effect Of Linkages In The Hierarchical Clustering Of Auto-Regressive Algorithm For Defect Identification In Heat Exchanger Tubes

    The Effect Of Linkages In The Hierarchical Clustering Of Auto-Regressive Algorithm For Defect Identification In Heat Exchanger Tubes by Abd Halim, Zakiah, Jamaludin, Nordin, Putra, Azma

    Published 2019
    “…Pattern recognition approach based on Auto-Regressive (AR) algorithm is an alternative way to provide a more accurate defect identification from stress wave propagated along ASTM A179 heat exchanger tubes. …”
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  6. 6
    Implementation of Frequency Drift for Identification of Solar Radio Burst Type II

    Implementation of Frequency Drift for Identification of Solar Radio Burst Type II by Afandi, N.Z.M., Abidin, Z.Z., Umar, R., Sabri, N.H., Ibrahim, Z.A., Monstein, C.

    Published 2016
    “…The value of frequency drift was used as the main idea in this auto classify algorithm because it can easily implemented using MATLAB. …”
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  7. 7
    Nonlinear auto-regressive model structure selection using binary particle swarm optimization algorithm / Ahmad Ihsan Mohd Yassin

    Nonlinear auto-regressive model structure selection using binary particle swarm optimization algorithm / Ahmad Ihsan Mohd Yassin by Mohd Yassin, Ahmad Ihsan

    Published 2014
    “…The identification process of NARX/NARMA/NARMAX involves structure selection and parameter estimation, which can be simultaneously performed using the widely accepted Orthogonal Least Squares (OLS) algorithm. …”
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  8. 8
    Comparative study between ARX and ARMAX system identification

    Comparative study between ARX and ARMAX system identification by Piltan, Farzin, TayebiHaghighi, Shahnaz, Sulaiman, Nasri

    Published 2017
    “…System Identification is used to build mathematical models of a dynamic system based on measured data. …”
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  9. 9
    Deterministic Mutation-Based Algorithm for Model Structure Selection in Discrete-Time System Identification

    Deterministic Mutation-Based Algorithm for Model Structure Selection in Discrete-Time System Identification by Abd Samad, Md Fahmi

    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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  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 Jamaluddin, Hishamuddin, Abd. Samad, M. F., Ahmad, Robiah, Yaacob, M. S.

    Published 2007
    “…This paper investigates the optimum grouping of chromosomes by fixed group ratios, enabling more efficient identification of dynamic systems using a NARX (Non-linear AutoRegressive with eXogenous input) model. …”
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  11. 11
    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
    “…This paper investigates the optimum grouping of chromosomes by fixed group ratios, enabling more efficient identification of dynamic systems using a NARX (Non-linear AutoRegressive with eXogenous input) model. …”
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  12. 12
    Discrete-Time System Identification Based On Novel Information Criterion Using Genetic Algorithm

    Discrete-Time System Identification Based On Novel Information Criterion Using Genetic Algorithm by Abd Samad, Md Fahmi, Mohd Nasir, Abdul Rahman

    Published 2017
    “…This paper investigates the identification of dynamic system in the form of NARX (Non-linear AutoRegressive with eXogenous input) model based on PMIC2 and AIC using GA. …”
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  13. 13
    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
    “…This paper investigates the optimum grouping of chromosomes by fixed group ratios, enabling more efficient identification of dynamic systems using a NARX (Non-linear AutoRegressive with eXogenous input) model. …”
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  14. 14
    Small-scale helicopter system identification model using recurrent neural networks

    Small-scale helicopter system identification model using recurrent neural networks by Taha, Z., Deboucha, A., Dahari, M.

    Published 2010
    “…The identification process is conducted by using the well known Levenberg-Marquardt learning algorithm. …”
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  15. 15
    RSA Encryption & Decryption using JAVA

    RSA Encryption & Decryption using JAVA by Ramli, Marliyana

    Published 2006
    “…The implementation of this project will be based on Rapid Application Design Methodology (RAD) and will be more focusing on research and finding, ideas and the implementation of the algorithm, and finally running and testing the algorithm. …”
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  16. 16
    Implementation of Evolutionary Algorithms to Parametric Identification of Gradient Flexible Plate Structure

    Implementation of Evolutionary Algorithms to Parametric Identification of Gradient Flexible Plate Structure by Annisa, Jamali, Muhammad Hasbollah, Hassan, Lidyana, Roslan, Muhamad Sukri, Hadi

    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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  17. 17
    Implementation of Evolutionary Algorithms to Parametric Identification of Gradient Flexible Plate Structure

    Implementation of Evolutionary Algorithms to Parametric Identification of Gradient Flexible Plate Structure by Annisa, Jamali, Lidyana, Roslan, Muhammad Hasbollah, Hassan

    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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  18. 18
    Estimator and Controller Design for a Didactic Liquid Level system by System Identification Approach

    Estimator and Controller Design for a Didactic Liquid Level system by System Identification Approach by Kamarudin, Muhammad Nizam, Md Rozali, Sahazati

    Published 2010
    “…This manuscript is a piece of report on the identification of Didactic Liquid Level Systems. The term didactic is used as to enlighten the purpose of proto-typing liquid level system for educational use. …”
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  19. 19
    Nonlinear identification of a small scale unmanned helicopter using optimized NARX network with multiobjective differential evolution

    Nonlinear identification of a small scale unmanned helicopter using optimized NARX network with multiobjective differential evolution by Tijani, Ismaila B., Akmeliawati, Rini, Legowo, Ari, Budiyono, Agus

    Published 2014
    “…This study proposes a hybrid of conventional back propagation training algorithm for the NARX network and multiobjective differential evolution (MODE) algorithm for identification of a nonlinear model of an unmanned small scale helicopter from experimental flight data.The proposed hybrid algorithm was able to produce models with Pareto-optimal compromise between the design objectives. …”
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  20. 20
    Estimator and Controller Design for a Didactic Liquid Level system by System Identification Approach

    Estimator and Controller Design for a Didactic Liquid Level system by System Identification Approach by Kamarudin, Muhammad Nizam, Md Rozali, Sahazati

    Published 2010
    “…This manuscript is a piece of report on the identification of Didactic Liquid Level Systems. The term didactic is used as to enlighten the purpose of proto-typing liquid level system for educational use. …”
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