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  1. 1
    Comparison between multi-objective and single-objective optimization for the modeling of dynamic systems

    Comparison between multi-objective and single-objective optimization for the modeling of dynamic systems by Mohd Zakimi, Zakaria, Hishamuddin, Jamaluddin, Robiah, Ahmad, Sayed Mohammad Reza, Loghmanian

    Published 2013
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  2. 2
    The implications for ahybrid detection technique against malicious sqlattacks on web applications

    The implications for ahybrid detection technique against malicious sqlattacks on web applications by Bahjat Arif, Sarajaldeen Akram, Wani, Sharyar

    Published 2025
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  3. 3
    Nlfxlms and thf-nlfxlms algorithms for wiener-hammerstein nonlinear active noise control

    Nlfxlms and thf-nlfxlms algorithms for wiener-hammerstein nonlinear active noise control by Srazhidinov, Radik

    Published 2016
    “…However, this assumption may lead to inaccurate secondary path model. In this work, the modelling of acoustic path using FIR filters is incorporated for both algorithms for Wiener-Hammerstein structure. …”
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  4. 4
    Model structure selection for a discrete-time non-linear system using genetic algorithm

    Model structure selection for a discrete-time non-linear system using genetic algorithm by Ahmad, Robiah, Jamaluddin , Hishamuddin, Hussain, Mohd. Azlan

    Published 2004
    “…The performance of the proposed algorithm is also compared to the model developed using the orthogonal least squares (OLS) algorithm. …”
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  5. 5
    Model structure selection for a discrete-time non-linear system using a genetic algorithm

    Model structure selection for a discrete-time non-linear system using a genetic algorithm by Ahmad, R., Jamaluddin, H., Hussain, M. A.

    Published 2004
    “…The performance of the proposed algorithm is also compared to the model developed using the orthogonal least squares (OLS) algorithm. …”
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  6. 6
    Model structure selection for a discrete-time non-linear system using a genetic algorithm

    Model structure selection for a discrete-time non-linear system using a genetic algorithm by Ahmad, R., Jamaluddin, H., Hussain, M. A.

    Published 2004
    “…The performance of the proposed algorithm is also compared to the model developed using the orthogonal least squares (OLS) algorithm. …”
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  7. 7
    Harmony Search algorithm-based gasoline consumption modeling for Indonesia

    Harmony Search algorithm-based gasoline consumption modeling for Indonesia by Anggarani, Riesta, Watada, Junzo

    Published 2012
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  8. 8
    Active intelligent control of vibration of flexible plate structures

    Active intelligent control of vibration of flexible plate structures by Md Salleh, Salihatun

    Published 2011
    “…However, the non-model based AVC algorithms are faster than their model-based AVC counterparts.…”
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  9. 9
    Development of dynamic programming algorithm for maintenance scheduling problem

    Development of dynamic programming algorithm for maintenance scheduling problem by Zafira Adlia, Mohd Fauzi

    Published 2020
    “…Using the dynamic programming algorithm developed, the model was also able to recalculate alternative schedules by replacing unavailable teams with other teams to avoid delays. …”
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  10. 10
    Verification of correctness properties for aggregation behavior of swarm robotics system using spin model checker / Siti Shafinaz Ali

    Verification of correctness properties for aggregation behavior of swarm robotics system using spin model checker / Siti Shafinaz Ali by Ali, Siti Shafinaz

    Published 2015
    “…This research work focused on a developed swarm algorithm aimed at swarm aggregation. …”
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  11. 11
    Verification correctness properties for aggregation behavior of swarm robotics system using SPIN model checker / Siti Shafinaz Ali

    Verification correctness properties for aggregation behavior of swarm robotics system using SPIN model checker / Siti Shafinaz Ali by Ali, Siti Shafinaz

    Published 2015
    “…This research work focused on a developed swarm algorithm aimed at swarm aggregation. …”
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  12. 12
    Model structure selection for a discrete-time non-linear system using a genetic algorithm

    Model structure selection for a discrete-time non-linear system using a genetic algorithm by Ahmad, R., Jamaluddin, H., Hussain, Mohd Azlan

    Published 2004
    “…The performance of the proposed algorithm is also compared to the model developed using the orthogonal least squares (OLS) algorithm. …”
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  13. 13
    Modelling and optimisation of blood glucose control for type 1 diabetes using multi-parametric programming and model-based predictive control (mp-MPC) / Associate Professor Dr Ayub Md. Som

    Modelling and optimisation of blood glucose control for type 1 diabetes using multi-parametric programming and model-based predictive control (mp-MPC) / Associate Professor Dr Ayub... by Md. Som, Ayub

    Published 2014
    “…In doing so, Multi-Parametric Programming technique is used to develop the computer algorithm; whereas Model-Based Predictive Control (MPC) is adopted for the design of the controller. …”
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    Monograph
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  14. 14
    Protovoltaic boost DC/DC converter with adaptive perturb and observe-fuzzy maximum power point tracking algorithm

    Protovoltaic boost DC/DC converter with adaptive perturb and observe-fuzzy maximum power point tracking algorithm by Mohd Zainuri, Muhammad Ammirrul Atiqi

    Published 2013
    “…For comparison purpose,conventional perturb and observe, and fuzzy logic control algorithms were modelled too. In hardware development, the prototype was developed and tested to verify simulation work. …”
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  15. 15
    Development of a new method of crack modeling and prediction algorithm

    Development of a new method of crack modeling and prediction algorithm by Aibinu, Abiodun Musa, Shafie, Amir Akramin, Salami, Momoh Jimoh Emiyoka, Salami, Abdulazeez F., Bamgbopa, I. A., Lawal, Wahab Adetunji

    Published 2008
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    Proceeding Paper
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  16. 16
    Development of improved metaheuristic algorithms for modelling and control of a flexible manipulator system

    Development of improved metaheuristic algorithms for modelling and control of a flexible manipulator system by Nasir, Ahmad Nor Kasruddin, Ahmad, Mohd Ashraf, Raja Ismail, R. M.T., Muhammad Hamka, Embong

    Published 2019
    “…The developed algorithms are formulated based on a spiral model approach and a sine model approach. …”
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    Research Report
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  17. 17
    LASSO-type estimations for threshold autoregressive and heteroscedastic time series models.

    LASSO-type estimations for threshold autoregressive and heteroscedastic time series models. by Muhammad Jaffri Mohd Nasir

    Published 2020
    “…Furthermore, our CGD algorithms are also capable of estimating the pure GARCH model, unlike any similar algorithm for the same model in the literature. …”
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    UMK Etheses
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  18. 18
    An intelligent framework for modelling and active vibration control of flexible structures

    An intelligent framework for modelling and active vibration control of flexible structures by Mohd. Hashim, Siti Zaiton

    Published 2004
    “…This thesis presents investigations into the development of an intelligent framework for modelling and active vibration control (AVC) of flexible structures. …”
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  19. 19
    A new hybrid deep neural networks (DNN) algorithm for Lorenz chaotic system parameter estimation in image encryption

    A new hybrid deep neural networks (DNN) algorithm for Lorenz chaotic system parameter estimation in image encryption by Nurnajmin Qasrina Ann, Ayop Azmi

    Published 2023
    “…The research starts with developing the hybrid deep learning model consisting of DNN and a K-Means Clustering Algorithm. …”
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  20. 20
    Job shop rescheduling using a hybrid artificial immune system and genetic algorithm model

    Job shop rescheduling using a hybrid artificial immune system and genetic algorithm model by Mohamed Din, Aniza, Ku-Mahamud, Ku Ruhana, Yusof, Yuhanis, Mahmuddin, Massudi

    Published 2012
    “…This paper discusses on developing a hybrid model to tackle the problem of changing environment in the job shop scheduling problem.The main idea is to develop building blocks of partial schedules using the model developed that can be used to provide backup solutions when disturbances occur during production.This model hybridizes genetic algorithm (GA) with artificial immune systems (AIS) techniques to generate these partial schedules.Each partial schedule, also known as antibody, is assigned a fitness value for the selection of final population of best partial schedules. …”
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    Conference or Workshop Item
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