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  1. 1
    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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  2. 2
    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
    “…The LP’s application is need to be further computed with a technique and Simplex algorithm is the one that commonly used. The Simplex algorithm has three stages of computation namely initialization, iterative calculation and termination. …”
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  3. 3
    Evolution Performance of Symbolic Radial Basis Function Neural Network by Using Evolutionary Algorithms

    Evolution Performance of Symbolic Radial Basis Function Neural Network by Using Evolutionary Algorithms by Alzaeemi, Shehab Abdulhabib, Tay, Kim Gaik, Huong, Audrey, Sathasivam, Saratha, Majahar Ali, Majid Khan

    Published 2023
    “…It has been confirmed that the EP algorithm is quite effective in training and obtaining the best output weight, accompanied by the slightest iteration error, which minimizes the objective function of SRBFNN-2SAT.…”
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  4. 4
    Evolution Performance of Symbolic Radial Basis Function Neural Network by Using Evolutionary Algorithms

    Evolution Performance of Symbolic Radial Basis Function Neural Network by Using Evolutionary Algorithms by Shehab Abdulhabib Alzaeemi, Shehab Abdulhabib Alzaeemi, Kim Gaik Tay, Kim Gaik Tay, Audrey Huong, Audrey Huong, Saratha Sathasivam, Saratha Sathasivam, Majahar Ali, Majid Khan

    Published 2023
    “…It has been confirmed that the EP algorithm is quite effective in training and obtaining the best output weight, accompanied by the slightest iteration error, which minimizes the objective function of SRBFNN-2SAT.…”
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  5. 5
    Evolution Performance of Symbolic Radial Basis Function Neural Network by Using Evolutionary Algorithms

    Evolution Performance of Symbolic Radial Basis Function Neural Network by Using Evolutionary Algorithms by Shehab Abdulhabib Alzaeemi, Shehab Abdulhabib Alzaeemi, Kim Gaik Tay, Kim Gaik Tay, Audrey Huong, Audrey Huong, Saratha Sathasivam, Saratha Sathasivam, Majid Khan bin Majahar Ali, Majid Khan bin Majahar Ali

    Published 2023
    “…It has been confirmed that the EP algorithm is quite effective in training and obtaining the best output weight, accompanied by the slightest iteration error, which minimizes the objective function of SRBFNN-2SAT.…”
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  6. 6
    Evolution Performance of Symbolic Radial Basis Function Neural Network by Using Evolutionary Algorithms

    Evolution Performance of Symbolic Radial Basis Function Neural Network by Using Evolutionary Algorithms by Shehab Abdulhabib Alzaeemi, Shehab Abdulhabib Alzaeemi, Kim Gaik Tay, Kim Gaik Tay, Audrey Huong, Audrey Huong, Saratha Sathasivam, Saratha Sathasivam, Majahar Ali, Majid Khan

    Published 2023
    “…It has been confirmed that the EP algorithm is quite effective in training and obtaining the best output weight, accompanied by the slightest iteration error, which minimizes the objective function of SRBFNN-2SAT.…”
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  7. 7
    Evolution Performance of Symbolic Radial Basis Function Neural Network by Using Evolutionary Algorithms

    Evolution Performance of Symbolic Radial Basis Function Neural Network by Using Evolutionary Algorithms by Shehab Abdulhabib Alzaeemi, Shehab Abdulhabib Alzaeemi, Kim Gaik Tay, Kim Gaik Tay, Audrey Huong, Audrey Huong, Saratha Sathasivam, Saratha Sathasivam, Majahar Ali, Majid Khan

    Published 2023
    “…It has been confirmed that the EP algorithm is quite effective in training and obtaining the best output weight, accompanied by the slightest iteration error, which minimizes the objective function of SRBFNN-2SAT.…”
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  8. 8
    Evolution Performance of Symbolic Radial Basis Function Neural Network by Using Evolutionary Algorithms

    Evolution Performance of Symbolic Radial Basis Function Neural Network by Using Evolutionary Algorithms by Alzaeemi, Shehab Abdulhabib, Kim Gaik Tay, Kim Gaik Tay, Audrey Huong, Audrey Huong, Saratha Sathasivam, Saratha Sathasivam, Majahar Ali, Majid Khan

    Published 2023
    “…It has been confirmed that the EP algorithm is quite effective in training and obtaining the best output weight, accompanied by the slightest iteration error, which minimizes the objective function of SRBFNN-2SAT.…”
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  9. 9
    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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  10. 10
    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
    “…Overall, numerical results prove that these proposed methods are superior in terms of number of iterations and function evaluations. …”
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  11. 11
    Single Fitness Function to Optimize Energy using Genetic Algorithms for Wireless Sensor Network

    Single Fitness Function to Optimize Energy using Genetic Algorithms for Wireless Sensor Network by Ismail Abdullah, Kalid Abdlkader Marsal

    Published 2024
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  12. 12
    Optimization Of Pid Controller Using Grey Wolf Optimzer And Dragonfly Algorithm

    Optimization Of Pid Controller Using Grey Wolf Optimzer And Dragonfly Algorithm by Nik Mohamed Hazli, Nik Muhammad Aiman

    Published 2018
    “…However, to fully utilize the algorithm, the parameter of the algorithm need to be set properly. …”
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    Monograph
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  13. 13
    Master-leader-slave cuckoo search with parameter control for ANN optimization and its real-world application to water quality prediction

    Master-leader-slave cuckoo search with parameter control for ANN optimization and its real-world application to water quality prediction by Jaddi N.S., Abdullah S., Malek M.A.

    Published 2023
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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
    “…Moreover, to cope with dynamic environments, a combination of global and local path planning methods is introduced. The PSO algorithm functions as a global path planner, determining the complete path for each robot, whereas a sensor-based obstacle avoidance algorithm serves as a local planner to avoid collision with dynamic obstacles during navigation. …”
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  15. 15
    Comparative study of Conjugate Gradient methods under Armijo Line search / Nurfarahi Naabihah Mohd Azmi

    Comparative study of Conjugate Gradient methods under Armijo Line search / Nurfarahi Naabihah Mohd Azmi by Mohd Azmi, Nurfarahi Naabihah

    Published 2021
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  16. 16
    A Rough-Apriori Technique in Mining Linguistic Association Rules

    A Rough-Apriori Technique in Mining Linguistic Association Rules by Choo, Yun Huoy, Abu Bakar, Azuraliza, Hamdan, Abdul Razak

    Published 2008
    “…Five UCI datasets were tested in the 10-fold cross validation experiment settings. The frequent itemsets discovery in the Apriori algorithm was constrained to five iterations comparing to maximum iterations. …”
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  17. 17
    Comparative analysis of line search methods in the Steepest Descent algorithm for unconstrained optimization problems / Ahmad Zikri Shukeri, Puteri Qurratu Ain Megat Sulzamzamendi and Suhaida Ibrahim

    Comparative analysis of line search methods in the Steepest Descent algorithm for unconstrained optimization problems / Ahmad Zikri Shukeri, Puteri Qurratu Ain Megat Sulzamzamendi... by Shukeri, Ahmad Zikri, Megat Sulzamzamendi, Puteri Qurratu Ain, Ibrahim, Suhaida

    Published 2024
    “…The result from this study is choosing FMRI algorithm using exact line search to get faster convergence rate which means that the algorithm achieves a high level of accuracy in fewer iterations compared to using other algorithms and inexact line search.…”
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  18. 18
    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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  19. 19
    A modified technique in RFID networking planning and optimization

    A modified technique in RFID networking planning and optimization by Nawawi, Azli

    Published 2015
    “…In this research, PSO algorithm was used in the optimization process as it was considered as a very useful, efficient and well known algorithm. …”
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  20. 20
    Memoryless modified symmetric rank-one method for large-scale unconstrained optimization

    Memoryless modified symmetric rank-one method for large-scale unconstrained optimization by Modarres, Farzin, Abu Hassan, Malik, Leong, Wah June

    Published 2009
    “…Computational results, for a test set consisting of 73 unconstrained optimization problems, show that the proposed algorithm is very encouraging. …”
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