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  1. 1
    A modified crow search algorithm with niching technique for numerical optimization

    A modified crow search algorithm with niching technique for numerical optimization by Islam, J., Vasant, P.M., Negash, B.M., Watada, J.

    Published 2019
    “…The primitive crow search algorithm is a newly developed population-based algorithm which gained attention from the researchers of many fields as it needs only one parameter to be tuned. …”
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  2. 2
    A modified crow search algorithm with niching technique for numerical optimization

    A modified crow search algorithm with niching technique for numerical optimization by Islam, J., Vasant, P.M., Negash, B.M., Watada, J.

    Published 2019
    “…The primitive crow search algorithm is a newly developed population-based algorithm which gained attention from the researchers of many fields as it needs only one parameter to be tuned. …”
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  3. 3
    A modified n-th section line search in conjugate gradient methods for solving unconstrained optimization / Muhammad Imza Fakhri Jinudin

    A modified n-th section line search in conjugate gradient methods for solving unconstrained optimization / Muhammad Imza Fakhri Jinudin by Jinudin, Muhammad Imza Fakhri

    Published 2018
    “…These line search methods are tested based on six standard optimization test problems. …”
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  4. 4
    Identification of continuous-time model of hammerstein system using modified multi-verse optimizer

    Identification of continuous-time model of hammerstein system using modified multi-verse optimizer by Most. Julakha, Jahan Jui

    Published 2021
    “…his thesis implements a novel nature-inspired metaheuristic optimization algorithm, namely the modified Multi-Verse Optimizer (mMVO) algorithm, to identify the continuous-time model of Hammerstein system. …”
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  5. 5
    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
    “…In this study, we present a scaled memoryless modified Symmetric Rank-One (SR1) algorithm and investigate the numerical performance of the proposed algorithm for solving large-scale unconstrained optimization problems. …”
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  6. 6
    An improved electromagnetism-like algorithm for numerical optimization

    An improved electromagnetism-like algorithm for numerical optimization by Tan J.-D., Dahari M., Koh S.-P., Koay Y.-Y., Abed I.-A.

    Published 2023
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  7. 7
    New Quasi-Newton Equation And Method Via Higher Order Tensor Models

    New Quasi-Newton Equation And Method Via Higher Order Tensor Models by Gholilou, Fahimeh Biglari

    Published 2010
    “…Moreover, a new limited memory QN method to solve large scale unconstrained optimization is developed based on the modified BFGS updated formula. …”
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  8. 8
    A modified conjugate gradient coefficient with inexact line search for unconstrained optimization

    A modified conjugate gradient coefficient with inexact line search for unconstrained optimization by Mustafa, M., Aini, N., Rivaie, M

    Published 2016
    “…In this paper, we present a new CG method based on AMR∗ and CD method for solving unconstrained optimization functions. …”
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  9. 9
    Using Metaheuristics Algorithms (MHAs) to Optimize Water Supply Operation in Reservoirs: a Review

    Using Metaheuristics Algorithms (MHAs) to Optimize Water Supply Operation in Reservoirs: a Review by Almubaidin M.A.A., Ahmed A.N., Sidek L.B.M., Elshafie A.

    Published 2023
    Review
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  10. 10
    Numerical comparison between classical conjugate gradient and modified conjugate gradient / Mohd Afif Hamran

    Numerical comparison between classical conjugate gradient and modified conjugate gradient / Mohd Afif Hamran by Hamran, Mohd Afif

    Published 2018
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  11. 11
    Comparison of three modified Conjugate Gradient methods to solve unconstrained optimization problems / Siti Aminah Abdullah & Nur Anisah Najwa Mohd Arizi

    Comparison of three modified Conjugate Gradient methods to solve unconstrained optimization problems / Siti Aminah Abdullah & Nur Anisah Najwa Mohd Arizi by Abdullah, Siti Aminah, Mohd Arizi, Nur Anisah Najwa

    Published 2019
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  12. 12
    Parameter extraction of single, double, and three diodes photovoltaic model based on guaranteed convergence arithmetic optimization algorithm and modified third order Newton Raphson methods

    Parameter extraction of single, double, and three diodes photovoltaic model based on guaranteed convergence arithmetic optimization algorithm and modified third order Newton Raphson methods by Mohammed Ridha, Hussein, Hizam, Hashim, Mirjalili, Seyedali, Othman, Mohammad Lutfi, Ya'acob, Mohammad Effendy, Ahmadipour, Masoud

    Published 2022
    “…The proposed guaranteed convergence arithmetic optimization algorithm based on efficient modified third order Newton Raphson (GCAOAEmNR) method highlights important contributions to the literature in terms of methodology (explorer-exploiter phases) and objective function design. …”
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  13. 13
    A Descent Three-Term Conjugate Gradient Direction For Problems Of Unconstrained Optimization With Application

    A Descent Three-Term Conjugate Gradient Direction For Problems Of Unconstrained Optimization With Application by Sulaiman M. Ibrahim, Nur Idalisa, Norhaslinda Zullpakka, P. Kaelo, Norrlaili Shapiee

    Published 2026
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  14. 14
    Logistic regression methods for classification of imbalanced data sets

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

    Published 2012
    “…However, the imbalanced LR-based methods are not extensively developed such as imbalanced SVM-based methods. …”
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  15. 15
    Accurate numerical treatment on a stochastic SIR epidemic model with optimal control strategy

    Accurate numerical treatment on a stochastic SIR epidemic model with optimal control strategy by Ghosh, Indranil, Rashid, Muhammad Mahbubur, Ghosh, Pallabi, Mawa, Shukranul, Roy, Rupal, Ahsan, Md Manjurul, Gupta, Kishor Datta

    Published 2022
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  16. 16
    Smoothed functional algorithm with norm-limited update vector for identification of continuous-time fractional-order Hammerstein Models

    Smoothed functional algorithm with norm-limited update vector for identification of continuous-time fractional-order Hammerstein Models by Mok, Ren Hao, Mohd Ashraf, Ahmad

    Published 2024
    “…In particular, the standard smoothed functional algorithm (SFA) based method is modified by implementing a limit function in the update vector of the standard SFA based method to solve the issue of high tendency of divergence during the identification process. …”
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  17. 17
    A study on solution of matrix riccati differential equations using ant colony programming and simulink / Mohd Zahurin Mohamed Kamali

    A study on solution of matrix riccati differential equations using ant colony programming and simulink / Mohd Zahurin Mohamed Kamali by Mohamed Kamali, Mohd Zahurin

    Published 2015
    “…In this thesis, we implement the modified ant colony programming (ACP) algorithm for solving the matrix Riccati differential equation (MRDE). …”
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  18. 18
    Optimal Design of Damping Control of Oscillations in Power System Using Power System Stabilizers with Novel Improved BBO Algorithm

    Optimal Design of Damping Control of Oscillations in Power System Using Power System Stabilizers with Novel Improved BBO Algorithm by Kasilingam G., Pasupuleti J., Kasirajan S.K., Nagarathinam A., Natesan D.

    Published 2023
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  19. 19
    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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  20. 20
    Common benchmark functions for metaheuristic evaluation: a review

    Common benchmark functions for metaheuristic evaluation: a review by Hussain, Kashif, Mohd Salleh, Mohd Najib, Shi, Cheng, Naseem, Rashid

    Published 2017
    “…In literature, benchmark test functions have been used for evaluating performance of metaheuristic algorithms. Algorithms that perform well on a set of numerical optimization problems are considered as effective methods for solving real-world problems. …”
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