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  1. 1
    Interactive framework for dynamic modelling and active vibration control of flexible structures

    Interactive framework for dynamic modelling and active vibration control of flexible structures by Mat Darus, Intan Zaurah, Mohd. Hashim, Siti Zaiton, Tokhi, M. O.

    Published 2008
    “…The design and implementation of the interactive learning system incorporating the simulation algorithms, modelling and control strategies, are developed using MATLAB. …”
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  2. 2
    Dynamic path planning algorithm in mobile robot navigation

    Dynamic path planning algorithm in mobile robot navigation by Yun, S.C., Parasuraman, S., Ganapathy, V.

    Published 2011
    “…MATLAB simulation is developed to verify and validate the algorithm before they are real time implemented on Team AmigoBotTM robot. …”
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  3. 3
    A Bayesian parameter learning procedure for nonlinear dynamical systems via the ensemble Kalman filter

    A Bayesian parameter learning procedure for nonlinear dynamical systems via the ensemble Kalman filter by Ur Rehman, M.J., Dass, S.C., Asirvadam, V.S.

    Published 2018
    “…We develop a Markov Chain Monte Carlo (MCMC) algorithm, which is an iterative method, for parameter inference. …”
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  4. 4
    Polymorphic malware detection based on dynamic analysis and supervised machine learning / Nur Syuhada Selamat

    Polymorphic malware detection based on dynamic analysis and supervised machine learning / Nur Syuhada Selamat by Selamat, Nur Syuhada

    Published 2021
    “…The benefit of this work indicated that the implementation of a feature selection technique plays an important role in machine learning algorithms to increase the performance of detection.…”
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  5. 5
    Dynamic Bayesian networks and variable length genetic algorithm for designing cue-based model for dialogue act recognition

    Dynamic Bayesian networks and variable length genetic algorithm for designing cue-based model for dialogue act recognition by Yahya, Anwar Ali, Mahmod, Ramlan, Ramli, Abd Rahman

    Published 2010
    “…The model is, essentially, a dynamic Bayesian network induced from manually annotated dialogue corpus via dynamic Bayesian machine learning algorithms. …”
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  6. 6
    Evaluation of optimal MLP structure for heart disease diagnosis / Salbiah Ab Hamid

    Evaluation of optimal MLP structure for heart disease diagnosis / Salbiah Ab Hamid by Ab Hamid, Salbiah

    Published 2010
    “…ANN is biological inspired and it has dynamic characteristic which is learning. ANN is able to learn through experience and adaptation. …”
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  7. 7
    A Conceptual Framework to Aid Attribute Selection in Machine Learning Student Performance Prediction Models

    A Conceptual Framework to Aid Attribute Selection in Machine Learning Student Performance Prediction Models by Khan I., Ahmad A.R., Jabeur N., Mahdi M.N.

    Published 2023
    “…However, numerous barriers exist while developing and implementing such kind of learning analytics applications. …”
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  8. 8
    Deep continual learning for predicting blast-induced overbreak in tunnel construction / He Biao

    Deep continual learning for predicting blast-induced overbreak in tunnel construction / He Biao by He , Biao

    Published 2024
    “…The developed model is expected to possess the ability of continual learning, which is particularly advantageous in dynamic environments like tunnel blasting. …”
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  9. 9
    Fuzzy Mixed Assembly Line Sequencing and Scheduling Optimization Model Using Multiobjective Dynamic Fuzzy GA

    Fuzzy Mixed Assembly Line Sequencing and Scheduling Optimization Model Using Multiobjective Dynamic Fuzzy GA by Zahari, Taha, Farzad, Tahriri, Siti Zawiah, Md Dawal

    Published 2014
    “…In establishing the FAGA, five dynamic fuzzy parameter controllers are devised in which fuzzy expert experience controller (FEEC) is integrated with automatic learning dynamic fuzzy controller (ALDFC) technique. …”
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  10. 10
    Optimisation of fed-batch fermentation process using deep reinforcement learning

    Optimisation of fed-batch fermentation process using deep reinforcement learning by Chai, Wan Ying

    Published 2023
    “…In conclusion, a deep reinforcement learning algorithm was successfully developed for the substrate feeding rate optimisation in the fed-batch baker’s yeast fermentation process. …”
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  11. 11
    Reinforcement learning-based target tracking for unmanned aerial vehicle with achievement rewarding and multistage traning

    Reinforcement learning-based target tracking for unmanned aerial vehicle with achievement rewarding and multistage traning by Ahmed Abo Mosali, Najm Addin Mohammed

    Published 2022
    “…It requires handling a high level of nonlinearity and dynamics device. The aim is to enable accurate target tracking by UAV with responding to the dynamic generated by the target such as sudden trajectory change using reinforcement learning which is proved to learn dynamic effectively. …”
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  12. 12
    Chaos search in fourire amplitude sensitivity test

    Chaos search in fourire amplitude sensitivity test by Koda, Masato

    Published 2012
    “…This paper explores the characterization of learning functions involved in FAST and derives the underlying dynamical relationships with chaos search, which can provide new learning algorithms. …”
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  13. 13
    Chaos Search in Fourier Amplitude Sensitivity Test

    Chaos Search in Fourier Amplitude Sensitivity Test by Koda, Masato

    Published 2012
    “…This paper explores the characterization of learning functions involved in FAST and derives the underlying dynamical relationships with chaos search, which can provide new learning algorithms. …”
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  14. 14
    Development of deep reinforcement learning based resource allocation techniques in cloud radio access network

    Development of deep reinforcement learning based resource allocation techniques in cloud radio access network by Amjad, Iqbal

    Published 2022
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  15. 15
    New bio-inspired barnacle optimizers based least-square support vector machine for time-series prediction of pandemic outbreaks

    New bio-inspired barnacle optimizers based least-square support vector machine for time-series prediction of pandemic outbreaks by Marzia, Ahmed

    Published 2024
    “…By integrating evolutionary optimization with advanced machine learning techniques, these models offer potent solutions to effectively tackle the challenges posed by pandemics, such as the complex dynamics of COVID-19.…”
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  16. 16
    REAL-TIME ILLUMINATION COMPENSATION ON DYNAMIC BACKGROUND FOR CROWD ANALYTIC SURVEILLANCE

    REAL-TIME ILLUMINATION COMPENSATION ON DYNAMIC BACKGROUND FOR CROWD ANALYTIC SURVEILLANCE by MOHAMED AMEEN MASHOOD, MOHAMED ABUL HASSAN

    Published 2015
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  17. 17
    An augmented sequential MCMC procedure for particle based learning in dynamical systems

    An augmented sequential MCMC procedure for particle based learning in dynamical systems by Javvad ur Rehman, M., Dass, S.C., Asirvadam, V.S.

    Published 2019
    “…An augmented sequential Markov Chain Monte Carlo (ASMCMC) algorithm is developed for obtaining the posterior distribution of unknown parameters. …”
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  18. 18
    Optimization Of Two-Dimensional Dual Beam Scanning System Using Genetic Algorithms

    Optimization Of Two-Dimensional Dual Beam Scanning System Using Genetic Algorithms by Koh, Johnny Siaw Paw

    Published 2008
    “…Also, this research involves in developing a machine-learning system and program via genetic algorithm that is capable of performing independent learning capability and optimization for scanning sequence using novel GA operators. …”
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  19. 19
    Hyper-heuristic approaches for data stream-based iIntrusion detection in the Internet of Things

    Hyper-heuristic approaches for data stream-based iIntrusion detection in the Internet of Things by Hadi, Ahmed Adnan

    Published 2022
    “…Hence, the algorithm must overcome the problem of dynamic updates in the internal parameters or counter the concept drift. …”
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  20. 20
    Hybridization of metaheuristic algorithm in training radial basis function with dynamic decay adjustment for condition monitoring / Chong Hue Yee

    Hybridization of metaheuristic algorithm in training radial basis function with dynamic decay adjustment for condition monitoring / Chong Hue Yee by Chong , Hue Yee

    Published 2023
    “…In this research work, the motivation is to develop an autonomous learning model based on the hybridization of an adaptive ANN and a metaheuristic algorithm for optimizing ANN parameters so that the network could perform learning and adaptation in a more flexible way and handle condition classification tasks more accurately in industries, such as in power systems. …”
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