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  1. 1
    Simulated Kalman Filter: A Novel Estimation-based Metaheuristic Optimization Algorithm

    Simulated Kalman Filter: A Novel Estimation-based Metaheuristic Optimization Algorithm by Zuwairie, Ibrahim, Nor Hidayati, Abd Aziz, Nor Azlina, Ab. Aziz, Saifudin, Razali, Mohd Saberi, Mohamad

    Published 2016
    “…In this paper, a new population-based metaheuristic optimization algorithm, named Simulated Kalman Filter (SKF) is introduced. …”
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  2. 2
    Finite impulse response optimizers for solving optimization problems

    Finite impulse response optimizers for solving optimization problems by Ab Rahman, Tasiransurini

    Published 2019
    “…In this work, three new estimation-based metaheuristic algorithms are introduced. …”
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  3. 3
    Finite impulse response optimizers for solving optimization problems

    Finite impulse response optimizers for solving optimization problems by Tasiransurini, Ab Rahman

    Published 2019
    “…In this work, three new estimation-based metaheuristic algorithms are introduced. …”
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  4. 4
    Simultaneous computation of model order and parameter estimation for ARX model based on single swarm and multi swarm simulated Kalman filter

    Simultaneous computation of model order and parameter estimation for ARX model based on single swarm and multi swarm simulated Kalman filter by Kamil Zakwan, Mohd Azmi, Zuwairie, Ibrahim, Pebrianti, Dwi, Mohd Saberi, Mohamad

    Published 2017
    “…Simultaneous Model Order and Parameter Estimation (SMOPE) and Simultaneous Model Order and Parameter Estimation based on Multi Swarm (SMOPE-MS) are two techniques of implementing meta-heuristic algorithm to iteratively establish an optimal model order and parameters simultaneously for an unknown system. …”
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  5. 5
    A multiobjective simulated Kalman filter optimization algorithm

    A multiobjective simulated Kalman filter optimization algorithm by A. Azwan, A. Razak, Mohd Falfazli, Mat Jusof, Ahmad Nor Kasruddin, Nasir, Mohd Ashraf, Ahmad

    Published 2018
    “…SKF is a random based optimization algorithm inspired from Kalman Filter theory. …”
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  6. 6
    Pendulum-like algorithm as a local search technique

    Pendulum-like algorithm as a local search technique by Abed I.A., Koh S.P., Sahari K.S.M., Tiong S.K., Younis H.A.-K., Abed A.A.

    Published 2023
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  7. 7
    Guidance, navigation and control for satellite proximity operations using Tschauner-Hempel equations

    Guidance, navigation and control for satellite proximity operations using Tschauner-Hempel equations by Okasha, Mohamed Elsayed Aly Abd Elaziz, Newman, Brett

    Published 2011
    “…These algorithms are based on using the analytical closed-form solution of the Tschauner-Hempel equations that is completely explicit in time. …”
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  8. 8
    Guidance, navigation and control for satellite proximity operations using Tschauner-Hempel equations

    Guidance, navigation and control for satellite proximity operations using Tschauner-Hempel equations by Okasha, Mohamed Elsayed Aly Abd Elaziz, Newman, Brett

    Published 2014
    “…These algorithms are based on using the analytical closed-form solution of the Tschauner-Hempel equations that is completely explicit in time. …”
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  9. 9
    Liquid Flow Enhancement using Natural Polymeric Additives: Effect of Concentration

    Liquid Flow Enhancement using Natural Polymeric Additives: Effect of Concentration by Abdulbari, Hayder A., Fiona Ling, Wang Ming

    Published 2016
    “…In this paper, a new population-based metaheuristic optimization algorithm, named Simulated Kalman Filter (SKF) is introduced. …”
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  10. 10
    Adaptive differential evolution algorithm with fitness based selection of parameters and mutation strategies / Rawaa Dawoud Hassan Al-Dabbagh

    Adaptive differential evolution algorithm with fitness based selection of parameters and mutation strategies / Rawaa Dawoud Hassan Al-Dabbagh by Rawaa Dawoud Hassan, Al-Dabbagh

    Published 2015
    “…The simulation results show the effectiveness of the ARDE method over other conventional techniques, transcending the limits of the existing state-of-the-art algorithms in estimating the parameters of robot. …”
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  11. 11
    A Kalman Filter Approach for Solving Unimodal Optimization Problems

    A Kalman Filter Approach for Solving Unimodal Optimization Problems by Zuwairie, Ibrahim, Nor Hidayati, Abdul Aziz, Nor Azlina, Ab. Aziz, Saifudin, Razali, Mohd Ibrahim, Shapiai, Sophan Wahyudi, Nawawi, Mohd Saberi, Mohamad

    Published 2015
    “…In this paper, a new population-based metaheuristic optimization algorithm, named Simulated Kalman Filter (SKF) is introduced. …”
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  12. 12
    Relative motion guidance, navigation and control for autonomous spacecraft rendezvous

    Relative motion guidance, navigation and control for autonomous spacecraft rendezvous by Okasha, Mohamed Elsayed Aly Abd Elaziz, Newman, Brett

    Published 2011
    “…These algorithms are based on using the analytical closed-form solution of the Tschauner-Hempel equations that is completely explicit in time. …”
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  13. 13
    Development of optimization Alghorithm for uncertain non-linear dynamical system

    Development of optimization Alghorithm for uncertain non-linear dynamical system by Abdul Aziz, Mohd. Ismail, Yaacob, Nazeeruddin, Mohd. Said, Norfarizan, Hamzah, Nor Hazadura

    Published 2004
    “…Based on the results of these simulations, we compared the number of iterations needed by each algorithm to arrive at the optimal solution and the CPU time taken for each algorithm to execute the search. …”
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  14. 14
    An Adaptive Switching Cooperative Source Searching And Tracing Algorithms For Underwater Acoustic Source Localization

    An Adaptive Switching Cooperative Source Searching And Tracing Algorithms For Underwater Acoustic Source Localization by Majid, Mad Helmi Ab.

    Published 2019
    “…To adaptively switches between the two algorithms, an adaptive switching algorithm based on a Generalized Likelihood Ratio Test (GLRT) is proposed. …”
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  15. 15
    Parameter estimation of the cure fraction based on BCH model using left-censored data with covariates.

    Parameter estimation of the cure fraction based on BCH model using left-censored data with covariates. by I. Aljawadi, Bader Ahnad, Abu Bakar, Mohd Rizam, Ibrahim, Noor Akma, Midi, Habshah

    Published 2011
    “…The analysis is constructed by means of the exponential distribution in the case of left censoring and within the framework of the expectation maximization (EM) algorithm. The analysis provided the analytical solution and a simulation study for the cure rate parameter. …”
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  16. 16
    Physics-guided deep neural network to characterize non-Newtonian fluid flow for optimal use of energy resources

    Physics-guided deep neural network to characterize non-Newtonian fluid flow for optimal use of energy resources by Kumar, A., Ridha, S., Narahari, M., Ilyas, S.U.

    Published 2021
    “…The detailed parametric analysis exhibits the competency of the proposed algorithm to explain the rheological features. Monte-Carlo simulation is performed by propagating uncertainty to investigate the dominant parameters affecting simulated results. …”
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  17. 17
    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. Then, the developed algorithm is implemented to estimate the parameters of the Lorenz system. …”
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  18. 18
    An analytical approach on parametric estimation of cure fraction based on weibull distribution using interval censored data.

    An analytical approach on parametric estimation of cure fraction based on weibull distribution using interval censored data. by I. Aljawadi , Bader Ahmad, Abu Bakar, Mohd Rizam, Ibrahim, Noor Akma

    Published 2011
    “…Maximum likelihood estimation (MLE) method is proposed to estimate the parameters within the framework of expectation-maximization (EM) algorithm, Newton Raphson method also employed. …”
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  19. 19
    Parameter estimation of Kumaraswamy Burr type X models based on cure models with or without covariates

    Parameter estimation of Kumaraswamy Burr type X models based on cure models with or without covariates by Yusuf, Madaki Umar

    Published 2017
    “…In this thesis, we considered two methods via the classical maximum likelihood estimation (MLE) and the Bayes estimation using the Gibbs sampling (G-S) algorithm to estimate the parameters of BKBX, KBX and Beta-Weibull (BWB) models. …”
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  20. 20
    Application of boundary-fitted convolutional neural network to simulate non-Newtonian fluid flow behavior in eccentric annulus

    Application of boundary-fitted convolutional neural network to simulate non-Newtonian fluid flow behavior in eccentric annulus by Kumar, A., Ridha, S., Ilyas, S.U., Dzulkarnain, I., Pratama, A.

    Published 2022
    “…The algorithms also explain the effect of geometric and rheological parameters on the fluid flow attributes. …”
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