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  1. 1
    Schelkunoff array synthesis methods using adaptive-iterative algorithm

    Schelkunoff array synthesis methods using adaptive-iterative algorithm by Abdul Latiff, Nurul Mu'azzah

    Published 2003
    “…In doing sa, Schelkunoff Polynomial Method will be used in order to have z-domain information. …”
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  2. 2
    Improved Fast Fuzzy C-Means Algorithm for Medical MR Images Segmentation

    Improved Fast Fuzzy C-Means Algorithm for Medical MR Images Segmentation by Li, Min, Huang, Tinglei, Zhu, Gangqiang

    Published 2008
    “…This method fetches in statistic histogram information for minimizing the iteration times, and in the iteration process, the optimal number of clusters is automatically determined. …”
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  3. 3
    A memory-based gravitational search algorithm for enhancing minimum variance distortionless response beamforming

    A memory-based gravitational search algorithm for enhancing minimum variance distortionless response beamforming by Darzi S., Sieh Kiong T., Tariqul Islam M., Rezai Soleymanpour H., Kibria S.

    Published 2023
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  4. 4
    Optimal Power Flow Solution With Stochastic Renewable Energies Using Nature Inspired Algorithm

    Optimal Power Flow Solution With Stochastic Renewable Energies Using Nature Inspired Algorithm by Abdul Mu’iz Zulfadli, Ab Wahab

    Published 2022
    “…The use of the Moth Flame Optimization (MFO) algorithm to solve optimal power flow as an objective optimization problem in power system operation and control is described in this thesis. …”
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  5. 5
    Optimizing the placement of fire department in Kulim using greedy heuristic and simplex method / Muhammad Abu Syah Mohd Suzaly

    Optimizing the placement of fire department in Kulim using greedy heuristic and simplex method / Muhammad Abu Syah Mohd Suzaly by Mohd Suzaly, Muhammad Abu Syah

    Published 2023
    “…The first method is greedy heuristic method. Greedy heuristics is a type of optimization algorithm that makes decisions based on locally optimal solutions. …”
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  6. 6
    Proportional-integral control optimization using imperialist competitive algorithm

    Proportional-integral control optimization using imperialist competitive algorithm by Soheilirad, Mohammadsoroush

    Published 2012
    “…PID controller can be tuned using classical tuning techniques such as Iterative Methods, Direct Synthesis and Tuning Rules. …”
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  7. 7
    Augmented model based double iterative loop techniques for integrated system optimisation and parameter estimation of large scale industrial processes

    Augmented model based double iterative loop techniques for integrated system optimisation and parameter estimation of large scale industrial processes by Normah Abdullah, Brdys, M.A., Roberts, P.D.

    Published 1993
    “…The double iterative loop structures of the proposed algorithms use the real process measurement within the outer loops while the inner loops involve model based computation only. …”
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  8. 8
    Optimising neural network training efficiency through spectral parameter-based multiple adaptive learning rates

    Optimising neural network training efficiency through spectral parameter-based multiple adaptive learning rates by Yeong, Lin Koay, Hong, Seng Sim, Yong, Kheng Goh, Sing, Yee Chua, Wah, June Leong

    Published 2024
    “…Most optimization algorithms use a !xed learning rate or a simpli!…”
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  9. 9
    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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  10. 10
    SINR improvement using Firefly Algorithm (FA) for Linear Constrained Minimum Variance (LCMV) beamforming technique

    SINR improvement using Firefly Algorithm (FA) for Linear Constrained Minimum Variance (LCMV) beamforming technique by Doroody C., Tiong S.K., Darzi S.

    Published 2023
    “…Antennas; Arts computing; Beamforming; Bioluminescence; Energy efficiency; Fire protection; Image processing; Optimization; Signal interference; Signal to noise ratio; Beamforming technique; Business optimization; Firefly algorithms; Industrial optimization; Linear constrained minimum variances; Linearly constrained minimum variance; Meta heuristic algorithm; Signal to interference plus noise ratio; Iterative methods…”
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  11. 11
    Finite impulse response optimizers for solving optimization problems

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

    Published 2019
    “…Meanwhile, MAFIRO differs from AFIRO in terms of the iteration search strategy. These three algorithms are called in short as FIR optimizers (FIROs). …”
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  12. 12
    Finite impulse response optimizers for solving optimization problems

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

    Published 2019
    “…Meanwhile, MAFIRO differs from AFIRO in terms of the iteration search strategy. These three algorithms are called in short as FIR optimizers (FIROs). …”
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  13. 13
    A New Approach of Optimal Search Solution in Particle Swarm Optimization (PSO) Algorithm for Object Detection Method

    A New Approach of Optimal Search Solution in Particle Swarm Optimization (PSO) Algorithm for Object Detection Method by Zalili, Musa, Mohd Hafiz, Mohd Hassin, Nurul Izzatie Husna, Fauzi, Rohani, Abu Bakar, Watada, Junzo

    Published 2018
    “…Therefore, to overcome the several problems associated with the object detection method, a new approach in Particle Swarm Optimization (PSO) algorithm for optimal search solution as an alternative method to detect of object tracking quickly, precisely and accurately. …”
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  14. 14
    Modification of particle swarm optimization algorithm for optimization of discrete values

    Modification of particle swarm optimization algorithm for optimization of discrete values by Mohd Yassin, Ahmad Ihsan, Jusoh, Muhammad Huzaimy, Abdul Rahman, Farah Yasmin

    Published 2011
    “…Using this method, the optimization is still done in continuous form, but the solution is generated in discrete form. …”
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    Research Reports
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  15. 15
    Tree physiology optimization on SISO and MIMO PID control tuning

    Tree physiology optimization on SISO and MIMO PID control tuning by Halim, A.H., Ismail, I.

    Published 2018
    “…The iterative search of shoot towards better light supported by the root counterparts leads to an optimization idea of TPO algorithm. …”
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  16. 16
    Tree physiology optimization on SISO and MIMO PID control tuning

    Tree physiology optimization on SISO and MIMO PID control tuning by Halim, A.H., Ismail, I.

    Published 2018
    “…The iterative search of shoot towards better light supported by the root counterparts leads to an optimization idea of TPO algorithm. …”
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  17. 17
    Mussels wandering optimization algorithmn based training of artificial neural networks for pattern classification

    Mussels wandering optimization algorithmn based training of artificial neural networks for pattern classification by Abusnaina, Ahmed A., Abdullah, Rosni

    Published 2013
    “…Training an artificial neural network (ANN) is an optimization task since it is desired to find optimal neurons‘ weight of a neural network in an iterative training process. …”
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  18. 18
    Enhanced Flipping Technique to Reduce Variability in Image Steganography

    Enhanced Flipping Technique to Reduce Variability in Image Steganography by Kamil S., Abdullah S.N.H.S., Hasan M.K., Bohani F.A.

    Published 2023
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  19. 19
    Application of Newton-Gauss-Seidel method for solving multi-objective constrained optimization problems

    Application of Newton-Gauss-Seidel method for solving multi-objective constrained optimization problems by Peng Cheng, Jumat Sulaiman, Khadizah Ghazali

    Published 2024
    “…The second stage is to use the NewtonGauss-Seidel (NGS) iterative method to solve the transformed constrained optimization problem. …”
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  20. 20
    Impact of evolutionary algorithm on optimization of nonconventional machining process parameters

    Impact of evolutionary algorithm on optimization of nonconventional machining process parameters by B V, Raghavendra, R Annigiri, Anandkumar, Srikatamurthy, JS

    Published 2025
    “…Using a Python environment, three evolutionary algorithms such as, Particle Swarm Optimization (PSO), Ant Colony Optimization (ACO), and Firefly Algorithm (FA), were simulated to evaluate their effectiveness in minimizing surface roughness (Ra). …”
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