Search Results - (( using function methods algorithm ) OR ( parameter simulation modified algorithm ))

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  1. 1
    1D Multigrid Solver For Finite Element Method

    1D Multigrid Solver For Finite Element Method by Azhar, Mohamad Amiruddin

    Published 2022
    “…Next, the algorithm was modified by using a new Gauss-Seidel function. …”
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    Monograph
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  2. 2
    Numerical simulations of agent navigation via half-sweep modified two-parameter over-relaxation (HSMTOR)

    Numerical simulations of agent navigation via half-sweep modified two-parameter over-relaxation (HSMTOR) by F A Musli, Jumat Sulaiman, Azali Saudi

    Published 2021
    “…Thus, this study attempts to solve the route navigational problem iteratively via a numerical method. A new method called Half-Sweep Modified Two-Parameter Over-Relaxation (HSMTOR) is used to solve the navigational problems. …”
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  3. 3
    Fuzzy clustering method and evaluation based on multi criteria decision making technique

    Fuzzy clustering method and evaluation based on multi criteria decision making technique by Sameer, Fadhaa Othman

    Published 2018
    “…This proposed algorithm is developed based on heuristic method named modified binary particle swarm optimization (MBPSO) with kernel fuzzy clustering method as a fitness function. …”
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  4. 4
    Fast and optimal tuning of fractional order PID controller for AVR system based on memorizable-smoothed functional algorithm

    Fast and optimal tuning of fractional order PID controller for AVR system based on memorizable-smoothed functional algorithm by Ren Hao, Mok, Ahmad, Mohd Ashraf

    Published 2022
    “…Therefore, this study proposes a modified smoothed function algorithm (MSFA) based method to tune the FOPID controller of AVR system since it requires fewer number of function evaluation per iteration. …”
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  5. 5
    The effect of adaptive parameters on the performance of back propagation

    The effect of adaptive parameters on the performance of back propagation by Abdul Hamid, Norhamreeza

    Published 2012
    “…The Back Propagation algorithm or its variation on Multilayered Feedforward Networks is widely used in many applications. …”
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  6. 6
    Optimal power flow using the Jaya algorithm

    Optimal power flow using the Jaya algorithm by Warid, Warid, Hizam, Hashim, Mariun, Norman, Abdul Wahab, Noor Izzri

    Published 2016
    “…Unlike other population-based optimization methods, no algorithm-particular controlling parameters are required for this algorithm. …”
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  7. 7
    Parameter estimation of multicomponent transient signals using deconvolution and ARMA modelling techniques

    Parameter estimation of multicomponent transient signals using deconvolution and ARMA modelling techniques by Salami, Momoh Jimoh Emiyoka, Sidek, Shahrul Na'im

    Published 2003
    “…In this method of analysis the exponential signal is converted to a convolution model whose input is a train of weighted delta function that contains the signal parameters to be determined.The resolution of the estimated decay rates is poor if the conventional fast Fourier transform (FFT) algorithm is used to analyse the resulting deconvolved data. …”
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  8. 8
    A modified weight optimisation for higher-order neural network in time series prediction

    A modified weight optimisation for higher-order neural network in time series prediction by Husaini, Noor Aida

    Published 2020
    “…Since its discovery, the CS has been used extensively. However, these methods fixed the parameter values which essential for adjusting the weights. …”
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  9. 9
    Data-driven brain emotional learning-based intelligent controller-PID control of MIMO systems based on a modified safe experimentation dynamics algorithm

    Data-driven brain emotional learning-based intelligent controller-PID control of MIMO systems based on a modified safe experimentation dynamics algorithm by Shahrizal, Saat, Mohd Ashraf, Ahmad, Mohd Riduwan, Ghazali

    Published 2025
    “…The safe experimentation dynamics algorithm (SEDA) is one such method that optimizes controller parameters using data-driven techniques. …”
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  10. 10
    Data-driven brain emotional learning-based intelligent controller-PID control of MIMO systems based on a modified safe experimentation dynamics algorithm

    Data-driven brain emotional learning-based intelligent controller-PID control of MIMO systems based on a modified safe experimentation dynamics algorithm by Shahrizal, Saat, Mohd Ashraf, Ahmad, Mohd Riduwan, Ghazali

    Published 2025
    “…The safe experimentation dynamics algorithm (SEDA) is one such method that optimizes controller parameters using data-driven techniques. …”
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  11. 11
    Location determination using radio frequency RSSI and deterministic algorithm

    Location determination using radio frequency RSSI and deterministic algorithm by Hussin, A.G., Hassan, S.F., Zubairi, Y.Z., Zaharim, A., Sopian, K.

    Published 2008
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  12. 12
    PID CONTROLLER TUNING OF 3-PHASE SEPARATOR IN OIL & GAS INDUSTRY USING BACTERIA FORAGING OPTIMIZATION ALGORITHM

    PID CONTROLLER TUNING OF 3-PHASE SEPARATOR IN OIL & GAS INDUSTRY USING BACTERIA FORAGING OPTIMIZATION ALGORITHM by HO JOON , HENG

    Published 2012
    “…BFOA will be able to find the best parameters compared with the conventional methods and show better performance than PI control using trial and error method, PI control using Butterworth filter design method or IMC method. …”
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  13. 13
    Fair bandwidth distribution marking and scheduling algorithm in network traffic classification

    Fair bandwidth distribution marking and scheduling algorithm in network traffic classification by Al-Kharasani, Ameen Mohammed Abdulkarem

    Published 2019
    “…Finally, propose a new method of obtaining optimal parameters dropping functions for Random Early Detection (RED) algorithm. …”
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  14. 14
    Modelling of multi-robot system for search and rescue

    Modelling of multi-robot system for search and rescue by Poy, Yi Ler

    Published 2023
    “…This report focusses on developing a novel multi-robot path planning algorithm based on the Modified Particles Swarm Optimization (MPSO) algorithm for dynamic environments. …”
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  15. 15
    Using adaptive safe experimentation dynamics algorithm for maximizing wind farm power

    Using adaptive safe experimentation dynamics algorithm for maximizing wind farm power by Mohd Ashraf, Ahmad, Jui, Julakha Jahan, Mohd Riduwan, Ghazali

    Published 2022
    “…This research presents a model-free strategy for increasing wind farm power generation based on the Adaptive Safe Experimentation Dynamics Algorithm (ASEDA). The ASEDA method is an improved version of the Safe Experimentation Dynamics (SED) algorithm that modifies the current tuning variable to respond to the changes in the objective function. …”
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  16. 16
    Modeling the powder compaction process using the finite element method and inverse optimization

    Modeling the powder compaction process using the finite element method and inverse optimization by Hrairi, Meftah, Chtourou, Hedi, Gakwaya, Augustin, Guillot, Michel

    Published 2011
    “…Minimization of the objective function with respect to the material parameters was performed using an in-house optimization software shell built on a modified Levenberg–Marquardt method. …”
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  17. 17
    RMIL/AG: A new class of nonlinear conjugate gradient for training back propagation algorithm

    RMIL/AG: A new class of nonlinear conjugate gradient for training back propagation algorithm by Basri, S.M.M., Nawi, N.M., Mamat, M., Hamid, N.A.

    Published 2018
    “…This paper introduced a new class of efficient second order conjugate gradient (CG) for training BP called Rivaie, Mustafa, Ismail and Leong (RMIL)/AG. The RMIL uses the value of adaptive gain parameter in the activation function to modify the gradient based search direction. …”
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  18. 18
    Using adaptive safe experimentation dynamics algorithm for maximizing wind farm power production

    Using adaptive safe experimentation dynamics algorithm for maximizing wind farm power production by Mohd Ashraf, Ahmad, Jui, Julakha Jahan, Mohd Riduwan, Ghazali

    Published 2022
    “…This research presents a model-free strategy for increasing wind farm power generation based on the Adaptive Safe Experimentation Dynamics Algorithm (ASEDA). The ASEDA method is an improved version of the Safe Experimentation Dynamics (SED) algorithm that modifies the current tuning variable to respond to the changes in the objective function. …”
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  19. 19
    Bayesian survival and hazard estimates for Weibull regression with censored data using modified Jeffreys prior

    Bayesian survival and hazard estimates for Weibull regression with censored data using modified Jeffreys prior by Ahmed, Al Omari Mohammed

    Published 2013
    “…For the Weibull model with right censoring and unknown shape, the full conditional distribution for the scale and shape parameters are obtained via Gibbs sampling and Metropolis-Hastings algorithm from which the survival function and hazard function are estimated. …”
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  20. 20
    Comparison of mabsa, PSO and GWO of PI-PD controller for dc motor

    Comparison of mabsa, PSO and GWO of PI-PD controller for dc motor by Nur Naajihah, Ab Rahman

    Published 2024
    “…The swarm intelligence group selected Particle Swarm Optimization (PSO), Grey Wolf Optimization (GWO), and Modified Adaptive Bats Sonar Algorithms (MABSA) to optimize the parameters of the PI-PD controller. …”
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