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  1. 1
    Augmentation of basic-line-search and quick-simplex-method algorithms to enhance linear programming computational performance

    Augmentation of basic-line-search and quick-simplex-method algorithms to enhance linear programming computational performance by Nor Azlan, Nor Asmaa Alyaa

    Published 2021
    “…Each dataset is set to 10 different problems and the result of the iteration number was as follows: first datasets; new augmentation algorithm = 2, QSM = 4, BLSA = 7, and Simplex = 13 and second datasets; new augmentation algorithm = 1, QSM = 3, BLSA = 4, and Simplex = 8.…”
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  2. 2
    Attribute reduction based scheduling algorithm with enhanced hybrid genetic algorithm and particle swarm optimization for optimal device selection

    Attribute reduction based scheduling algorithm with enhanced hybrid genetic algorithm and particle swarm optimization for optimal device selection by Nwogbaga, Nweso Emmanuel, Latip, Rohaya, Affendey, Lilly Suriani, Abdul Rahiman, Amir Rizaan

    Published 2022
    “…The simulation is implemented with iFogSim and java programming language. …”
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  3. 3
    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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  4. 4
    Comparisons between Jacobi method, Gauss Seidel method and Successive Over Relaxation method / Wan Nashratudiniah Wan Hamad

    Comparisons between Jacobi method, Gauss Seidel method and Successive Over Relaxation method / Wan Nashratudiniah Wan Hamad by Wan Hamad, Wan Nashratudiniah

    Published 2021
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  5. 5
    Enhancement of Ant Colony Optimization for Grid Job Scheduling and Load Balancing

    Enhancement of Ant Colony Optimization for Grid Job Scheduling and Load Balancing by Husna, Jamal Abdul Nasir

    Published 2011
    “…Global pheromone update is performed after the completion of processing the jobs in order to reduce the pheromone value of resources. A simulation environment was developed using Java programming to test the performance of the proposed EACO algorithm against existing grid resource management algorithms such as Antz algorithm, Particle Swarm Optimization algorithm, Space Shared algorithm and Time Shared algorithm, in terms of processing time and resource utilization. …”
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  6. 6
    Ant colony optimization algorithm for load balancing in grid computing

    Ant colony optimization algorithm for load balancing in grid computing by Ku-Mahamud, Ku Ruhana, Mohamed Din, Aniza

    Published 2012
    “…The proposed algorithm is known as the enhance ant colony optimization (EACO). …”
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  7. 7
    Iterative methods for solving split common fixed point problems in Hilbert spaces

    Iterative methods for solving split common fixed point problems in Hilbert spaces by Mohammed, Lawan Bulama

    Published 2016
    “…We also suggest some iterative methods for solving the split common fixed point problems for the class of total quasi asymptotically nonexpansive mappings and prove the convergence results of the proposed algorithms. …”
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  8. 8
    Comparison Of Various Alogrithms In Different Loading Of Load Flow Analysis

    Comparison Of Various Alogrithms In Different Loading Of Load Flow Analysis by Tajudin, Nur Atikah

    Published 2018
    “…The set of nonlinear algebraic equations is solved using iteration methods. …”
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  9. 9
    Improved stochastic gradient descent algorithm with mean-gradient adaptive stepsize for solving large-scale optimization problems

    Improved stochastic gradient descent algorithm with mean-gradient adaptive stepsize for solving large-scale optimization problems by Zulkifli, Munierah, Abd Rahmin, Nor Aliza, Wah, June Leong

    Published 2023
    “…It is an iterative algorithm with descent properties that reduces computational cost by using derivatives of random data points. …”
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  10. 10
    Logistic regression methods for classification of imbalanced data sets

    Logistic regression methods for classification of imbalanced data sets by Santi Puteri Rahayu, -

    Published 2012
    “…These results can be seen as further explanation on the success of Truncated Newton method in TR-KLR and TR Iteratively Re-weighted Least Square (TR-IRLS) algorithm respectively, because of the equivalence of iterative method used by these algorithms. …”
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  11. 11
    Quasi-Newton type method via weak secant equations for unconstrained optimization

    Quasi-Newton type method via weak secant equations for unconstrained optimization by Lim, Keat Hee

    Published 2021
    “…Armijo condition is implemented in the algorithms to generate monotone property in each iteration. …”
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  12. 12
    An enhanced robust association rules method for missing values imputation in Arabic language data set

    An enhanced robust association rules method for missing values imputation in Arabic language data set by Salem, Awsan Thabet

    Published 2023
    “…This method deals with high missing value rates by adjusting the support threshold in every iteration of the algorithm. …”
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  13. 13
    Quantitative study of iterative reconstruction algorithms of spect/ct in bone scan: a clinical and phantom study

    Quantitative study of iterative reconstruction algorithms of spect/ct in bone scan: a clinical and phantom study by Hao, Lau Lik

    Published 2024
    “…This study evaluates the impact of iterative reconstruction algorithms with various attenuation correction methods on SPECT quantification accuracy and image quality in bone scan across different iteration numbers in both phantom and clinical settings. …”
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  14. 14
    Identification of manipulator kinematics parameters through iterative method

    Identification of manipulator kinematics parameters through iterative method by Baharin, Iskandar, Hasan, Md. Mahmud

    “…To achieve the objective, an iterative based optimization technique was formulated which minimizes the Cartesian positioning of a manipulator by determining its rigid geometrical parameters such as the link lengths, twists, and off-sets joint angles. …”
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  15. 15
    Two dimensional datamodeling and Chebyshev approximation of spline

    Two dimensional datamodeling and Chebyshev approximation of spline by Fauziahanim, Che Seman, ShahNor, Basri, Ahmad Faizal, Mohd Zain

    Published 2011
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  16. 16
    Semiparametric inference procedure for the accelarated failure time model with interval-censored data

    Semiparametric inference procedure for the accelarated failure time model with interval-censored data by Karimi, Mostafa

    Published 2019
    “…Also, a one-step iterative algorithm, called expected rank algorithm, is introduced which is more complicated than the estimation-approximation algorithm, but more accurate. …”
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  17. 17
    OPTIMIZED MIN-MIN TASK SCHEDULING ALGORITHM FOR SCIENTIFIC WORKFLOWS IN A CLOUD ENVIRONMENT

    OPTIMIZED MIN-MIN TASK SCHEDULING ALGORITHM FOR SCIENTIFIC WORKFLOWS IN A CLOUD ENVIRONMENT by Murad S.S., Badeel R., Alsandi N.S.A., Alshaaya R.F., Ahmed R.A., Muhammed A., Derahman M.

    Published 2023
    “…To achieve this, we propose a new noble mechanism called Optimized Min-Min (OMin-Min) algorithm, inspired by the Min-Min algorithm. …”
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  18. 18
    New Iterative method for solving fuzzy nonlinear equation

    New Iterative method for solving fuzzy nonlinear equation by Amirah, Ramli, Mohd Lazim, Abdullah, Mustafa, Mamat

    Published 2010
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  19. 19
    Logistic Regression Methods with Truncated Newton Method

    Logistic Regression Methods with Truncated Newton Method by Jasni, Mohamad Zain, Abdullah, Embong, Rahayu, Santi Puteri, Juwari, S, Purnami, Santi Wulan

    Published 2012
    “…While proposed NTR-LR has performed better training time than RLR with Newton-Raphson (RLR-NR) method on Letter Image data set. Moreover, both proposed algorithms have showed consistency with the convergence theory and have promising results, i.e. accurate and stable classification, on image data sets respectively.…”
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  20. 20
    Computer-generated fractals with medical application in trabecular bone structure / Hizmawati Madzin

    Computer-generated fractals with medical application in trabecular bone structure / Hizmawati Madzin by Hizmawati , Madzin

    Published 2006
    “…FGS generates four types of fractals, which are Julia set, Mandelbrot set, Sierpinski Triangle and Koch Snowflake based on the three iterations. …”
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