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  1. 1
    A firefly algorithm based hybrid method for structural topology optimization

    A firefly algorithm based hybrid method for structural topology optimization by Gebremedhen, H.S., Woldemichael, D.E., Hashim, F.M.

    Published 2020
    “…Since the direct application of the firefly algorithm cannot generate connected topologies, outputs from the firefly algorithm were used as an initial input material distribution for the OC method. …”
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  2. 2
    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
    “…The proposed algorithm is used as a pre-processing method for data followed by Gustafson-Kessel (GK) algorithm to classify credit scoring data. …”
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  3. 3
    Efficient genetic partitioning-around-medoid algorithm for clustering

    Efficient genetic partitioning-around-medoid algorithm for clustering by Garib, Sarmad Makki Mohammed

    Published 2019
    “…Lastly, in order to externally judge the validity of these types of clustering algorithms, there is a need for a method to correctly and efficiently evaluate their variant multiclass clustering results. …”
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  4. 4
    Shooting method with root finding to solve boundary value problems / Aryani Rima Matakim

    Shooting method with root finding to solve boundary value problems / Aryani Rima Matakim by Matakim, Aryani Rima

    Published 2025
    “…In this study, the result of the shooting method combined with various root-finding algorithms such as the Bisection method, Secant method, Newton's method, Ridder's method, Halley’s method, Brent’s method, Modified Newton method and Improved Ostrowski’s method to solve BVPs is evaluated. …”
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  5. 5
    Clustering ensemble learning method based on incremental genetic algorithms

    Clustering ensemble learning method based on incremental genetic algorithms by Ghaemi, Reza

    Published 2012
    “…In the first and second phases, a threshold fuzzy c-means clustering algorithm as a clusterer and a pattern ensemble learning method based on the incremental genetic-based algorithms are proposed respectively. …”
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  6. 6
    Studying the Impact of Initialization for Population-Based Algorithms with Low-Discrepancy Sequences

    Studying the Impact of Initialization for Population-Based Algorithms with Low-Discrepancy Sequences by Adnan Ashraf, Sobia Pervaiz, Waqas Haider Bangyal, Kashif Nisar, Ag. Asri Ag. Ibrahim, Joel J. P. C. Rodrigues, Danda B. Rawat

    Published 2021
    “…To solve different kinds of optimization challenges, meta-heuristic algorithms have been extensively used. Population initialization plays a prominent role in meta-heuristic algorithms for the problem of optimization. …”
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  7. 7
    Comparison between Newton’s Method and a new Scaling Newton Method / Ramizah Baharuddin

    Comparison between Newton’s Method and a new Scaling Newton Method / Ramizah Baharuddin by Baharuddin, Ramizah

    Published 2021
    “…Newton's Method also called the Newton-Raphson method is a recursive algorithm for approximating the root of a differentiable function. …”
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  8. 8
    An optimized wavelet neural networks using cuckoo search algorithm for function approximation and chaotic time series prediction

    An optimized wavelet neural networks using cuckoo search algorithm for function approximation and chaotic time series prediction by Pauline Ong, Pauline Ong, Zainuddin, Zarita

    Published 2023
    “…Performance assessment demonstrates its superior approximation capability than the existing methods used for WNNs initialization.…”
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  9. 9
    An optimized wavelet neural networks using cuckoo search algorithm for function approximation and chaotic time series prediction

    An optimized wavelet neural networks using cuckoo search algorithm for function approximation and chaotic time series prediction by Pauline Ong, Pauline Ong, Zainuddin, Zarita

    Published 2023
    “…Performance assessment demonstrates its superior approximation capability than the existing methods used for WNNs initialization.…”
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  10. 10
    An optimized wavelet neural networks using cuckoo search algorithm for function approximation and chaotic time series prediction

    An optimized wavelet neural networks using cuckoo search algorithm for function approximation and chaotic time series prediction by Pauline Ong, Pauline Ong, Zainuddin, Zarita

    Published 2023
    “…Performance assessment demonstrates its superior approximation capability than the existing methods used for WNNs initialization.…”
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  11. 11
    An optimized wavelet neural networks using cuckoo search algorithm for function approximation and chaotic time series prediction

    An optimized wavelet neural networks using cuckoo search algorithm for function approximation and chaotic time series prediction by Pauline Ong, Pauline Ong, Zainuddin, Zarita

    Published 2023
    “…Performance assessment demonstrates its superior approximation capability than the existing methods used for WNNs initialization.…”
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  12. 12
    An optimized wavelet neural networks using cuckoo search algorithm for function approximation and chaotic time series prediction

    An optimized wavelet neural networks using cuckoo search algorithm for function approximation and chaotic time series prediction by Pauline Ong, Pauline Ong, Zainuddin, Zarita

    Published 2023
    “…Performance assessment demonstrates its superior approximation capability than the existing methods used for WNNs initialization.…”
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  13. 13
    An optimized wavelet neural networks using cuckoo search algorithm for function approximation and chaotic time series prediction

    An optimized wavelet neural networks using cuckoo search algorithm for function approximation and chaotic time series prediction by Pauline Ong, Pauline Ong, Zainuddin, Zarita

    Published 2023
    “…Performance assessment demonstrates its superior approximation capability than the existing methods used for WNNs initialization.…”
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  14. 14
    Parallel execution of diagonally implicit Runge-Kutta methods for solving IVPs.

    Parallel execution of diagonally implicit Runge-Kutta methods for solving IVPs. by Ismail, Fudziah, Siri, Zailan, Othman, Mohamad, Suleiman, Mohamed

    Published 2009
    “…Diagonally Implicit Runge-Kutta (DIRK) methods are amongst the most useful and cost-effective methods for solving initial value problems but the dependency of the functions evaluations on the previous functions evaluations makes DIRK method not so favourable for parallel computers. …”
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  15. 15
    Improved hybrid methods in solving single variable nonlinear algebraic equations / Nor Hanim Abd Rahman

    Improved hybrid methods in solving single variable nonlinear algebraic equations / Nor Hanim Abd Rahman by Abd Rahman, Nor Hanim

    Published 2017
    “…Two sets of schemes of hybrid algorithms, the Higher Order Taylor-Perturbation method (HTP) and Higher Order Homotopy Taylor Perturbation method (HHTP) with higher order correctional terms up to 6th order are derived and evaluated. …”
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  16. 16
    An Integrated RRT*SMART-A* Algorithm for solving the Global Path Planning Problem in a Static Environment

    An Integrated RRT*SMART-A* Algorithm for solving the Global Path Planning Problem in a Static Environment by Suwoyo, Heru, Adriansyah, Andi, Andika, Julpri, Ubaidillah, Abu

    Published 2023
    “…However, before RRT*-Smart is combined with A*, it is improved by replacing the random sampling method with Fast Sampling. In short, by involving A*, the exploration process for generating the Smart-RRT*’s initial path can be supported. …”
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  17. 17
    AN INTEGRATED RRT*SMART-A* ALGORITHM FOR SOLVING THE GLOBAL PATH PLANNING PROBLEM IN A STATIC ENVIRONMENT

    AN INTEGRATED RRT*SMART-A* ALGORITHM FOR SOLVING THE GLOBAL PATH PLANNING PROBLEM IN A STATIC ENVIRONMENT by SUWOYO, HERU, ADRIANSYAH, ANDI, ANDIKA, JULFRI, SHAMSUDIN, ABU UBAIDAH, ZAKARIA, MOHAMAD FAUZI

    Published 2023
    “…However, before RRT*-Srnart is combined •...ith A*, it is improved by replacing the random sampling method with Fast Sampling. In short, by involving A*. the exploration process for generating the .mart-RRT*'s initial path can be supported. …”
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  18. 18
    AN INTEGRATED RRT*SMART-A* ALGORITHM FOR SOLVING THE GLOBAL PATH PLANNING PROBLEM IN A STATIC ENVIRONMENT

    AN INTEGRATED RRT*SMART-A* ALGORITHM FOR SOLVING THE GLOBAL PATH PLANNING PROBLEM IN A STATIC ENVIRONMENT by Suwayo, Heri, Adrishah, Andi, Andika, Juleri, Shamdudin, Abu Ubaidah, Zakaria, Mohamad Fauzi

    Published 2023
    “…However, before RRT*-Srnart is combined •...ith A*, it is improved by replacing the random sampling method with Fast Sampling. In short, by involving A*. the exploration process for generating the .mart-RRT*'s initial path can be supported. …”
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  19. 19
    AN INTEGRATED RRT*SMART-A* ALGORITHM FOR SOLVING THE GLOBAL PATH PLANNING PROBLEM IN A STATIC ENVIRONMENT

    AN INTEGRATED RRT*SMART-A* ALGORITHM FOR SOLVING THE GLOBAL PATH PLANNING PROBLEM IN A STATIC ENVIRONMENT by SUWOYO, HERU, ADRIANSHAH, ANDI, ANDIKA, JULPRI, SHAMSUDIN, ABU UBAIDAH, ZAKARIA, MOHAMAD FAUZI

    Published 2023
    “…However, before RRT*-Srnart is combined •...ith A*, it is improved by replacing the random sampling method with Fast Sampling. In short, by involving A*. the exploration process for generating the .mart-RRT*'s initial path can be supported. …”
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  20. 20
    Optimizing decentralized exam timetabling with a discrete whale optimization algorithm

    Optimizing decentralized exam timetabling with a discrete whale optimization algorithm by Emily Sing Kiang Siew, San nah sze, Say leng goh

    Published 2025
    “…This problem remains an active area of research and, to the authors' knowledge, has not been adequately addressed by the WOA algorithm. The method was evaluated using real-world data from the first semester of 2023/2024 for faculties at the Universiti of Sarawak, Malaysia. …”
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