Search Results - (( parallel solution machine algorithm ) OR ( parameter optimization based algorithm ))

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  1. 1
    Multi-objectives process optimization in end milling process of aluminium alloy 6061-T6 using genetic algorithm

    Multi-objectives process optimization in end milling process of aluminium alloy 6061-T6 using genetic algorithm by W., Safiei, Rahman, M. M., M.Y., Ali

    Published 2024
    “…For future study, other methods or algorithms can be applied in other machining processes to obtain optimum machining parameters.…”
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  2. 2
    Deep Learning-Driven Mobility And Utility-Based Resource Management In Mm-Wave Enable Ultradense Heterogeneous Networks

    Deep Learning-Driven Mobility And Utility-Based Resource Management In Mm-Wave Enable Ultradense Heterogeneous Networks by Ukasyah bin Mahamod

    Published 2025
    thesis::doctoral thesis
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  3. 3
    Hybridizing guided genetic algorithm and single-based metaheuristics to solve unrelated parallel machine scheduling problem with scarce resources

    Hybridizing guided genetic algorithm and single-based metaheuristics to solve unrelated parallel machine scheduling problem with scarce resources by Abed, Munther H., Mohd Nizam, Mohmad Kahar

    Published 2023
    “…This paper focuses on solving unrelated parallel machine scheduling with resource constraints (UPMR). …”
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  4. 4
    Fast Finite Difference Time Domain Algorithms for Solving Antenna Application Problem

    Fast Finite Difference Time Domain Algorithms for Solving Antenna Application Problem by Hasan, Mohammad Khatim

    Published 2008
    “…Results show that these new sequential and parallel algorithms run faster than the standard sequential and parallel FDTD algorithms. …”
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  5. 5
    Parallel block methods for solving higher order ordinary differential equations directly

    Parallel block methods for solving higher order ordinary differential equations directly by Omar, Zurni

    Published 1999
    “…Hence, the development of parallel algorithms to suit these machines becomes essential. …”
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  6. 6
    Flexible job shop scheduling using priority heuristics and genetic algorithm

    Flexible job shop scheduling using priority heuristics and genetic algorithm by Farashahi, Hamid Ghaani

    Published 2010
    “…The job shop scheduling is very common in practice and uniform machines (parallel machines with different speeds) have been used in job shop environment for flexibility. …”
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  7. 7
    Tumor growth prediction using parallel computing: numerical solutions based on multi-dimensional partial differential equation (PDE)

    Tumor growth prediction using parallel computing: numerical solutions based on multi-dimensional partial differential equation (PDE) by Alias, Norma, Islam, Md. Rajibul

    Published 2010
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  8. 8
    Parallel CFD Simulations of Multiphase Systems: Jet into a Cylindrical Bath and Rotary Drum on a Rectangular Bath.

    Parallel CFD Simulations of Multiphase Systems: Jet into a Cylindrical Bath and Rotary Drum on a Rectangular Bath. by Hasan, Nurul

    Published 2001
    “…For commercial CFD packages, in many cases the solution algorithms are black boxes, even though parallel computing helps in many cases to overcome the limitations, as shown here. …”
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  9. 9
    Parallel power load abnormalities detection using fast density peak clustering with a hybrid canopy-K-means algorithm

    Parallel power load abnormalities detection using fast density peak clustering with a hybrid canopy-K-means algorithm by Al-Jumaili A.H.A., Muniyandi R.C., Hasan M.K., Singh M.J., Paw J.K.S., Al-Jumaily A.

    Published 2025
    “…Parallel power loads anomalies are processed by a fast-density peak clustering technique that capitalizes on the hybrid strengths of Canopy and K-means algorithms all within Apache Mahout's distributed machine-learning environment. …”
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  10. 10
    Intelligent classification algorithms in enhancing the performance of support vector machine

    Intelligent classification algorithms in enhancing the performance of support vector machine by Alwan, Hiba Basim, Ku-Mahamud, Ku Ruhana

    Published 2019
    “…This can be achieved by simultaneously executing the selection of feature subset and tuning SVM parameters simultaneously. The algorithms are called ACOMVSVM and IACOMV-SVM. The difference between the algorithms is the size of the solution archive. …”
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  11. 11
    Parallel R-point implicit block method for solving higher order ordinary differential equations directly

    Parallel R-point implicit block method for solving higher order ordinary differential equations directly by Omar, Zurni, Sulaiman, M.

    Published 2004
    “…Hence, the development of parallel algorithms to suit these machines becomes essential. …”
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  12. 12
    A parallel ensemble learning model for fault detection and diagnosis of industrial machinery

    A parallel ensemble learning model for fault detection and diagnosis of industrial machinery by Shing, Chiang Ta, Mohammed Al-Andoli, Mohammed Nasser, Kok, Swee Sim, Seera, Manjeevan, Chee, Peng Lim

    Published 2023
    “…However, the gradient descent optimization method that is commonly used in deep learning suffers from several limitations, such as high computational cost and local sub-optimal solutions. Accordingly, this paper proposes a new parallel ensemble model comprising hybrid machine and deep learning for undertaking FDD tasks. …”
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  13. 13
    Measuring GPU-accelerated parallel SVM performance using large datasets for multi-class machine learning problem

    Measuring GPU-accelerated parallel SVM performance using large datasets for multi-class machine learning problem by Sulaiman M.A.H.B., Suliman A., Ahmad A.R.

    Published 2023
    Conference Paper
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  14. 14
    Topology-aware hypergraph based approach to optimize scheduling of parallel applications onto distributed parallel architectures

    Topology-aware hypergraph based approach to optimize scheduling of parallel applications onto distributed parallel architectures by Koohi, Sina Zangbari

    Published 2020
    “…However, the current meta-heuristic algorithms do not ensure an optimum solution within a reasonable time. …”
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  15. 15
    Integrated optimal control and parameter estimation algorithms for discrete-time nonlinear stochastic dynamical systems

    Integrated optimal control and parameter estimation algorithms for discrete-time nonlinear stochastic dynamical systems by Kek, Sie Long

    Published 2011
    “…The main idea is the integration of optimal control and parameter estimation. In this work, a simplified model-based optimal control model with adjustable parameters is constructed. …”
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  16. 16
    On Adopting Parameter Free Optimization Algorithms for Combinatorial Interaction Testing

    On Adopting Parameter Free Optimization Algorithms for Combinatorial Interaction Testing by Kamal Z., Zamli, Alsariera, Yazan A., Nasser, Abdullah B., Alsewari, Abdulrahman A.

    Published 2015
    “…In doing so, this paper reviews two existing parameter free optimization algorithms involving Teaching Learning Based Optimization (TLBO) and Fruitfly Optimization Algorithm (FOA) in an effort to promote their adoption for CIT.…”
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  17. 17
    Finite impulse response optimizers for solving optimization problems

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

    Published 2019
    “…Selecting optimal parameters’ values may improve an algorithm’s performance. …”
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  18. 18
    Finite impulse response optimizers for solving optimization problems

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

    Published 2019
    “…Selecting optimal parameters’ values may improve an algorithm’s performance. …”
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  19. 19
    Paralell R-point implicit block method for solving higher order ordinary differential equations directly

    Paralell R-point implicit block method for solving higher order ordinary differential equations directly by Omar, Zurni, Sulaiman, M.

    Published 2004
    “…Hence, the development of parallel algorithms to suit these machines becomes essential. …”
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  20. 20
    LS-SVM Hyper-parameters Optimization Based on GWO Algorithm for Time Series Forecasting

    LS-SVM Hyper-parameters Optimization Based on GWO Algorithm for Time Series Forecasting by Zuriani, Mustaffa, Mohd Herwan, Sulaiman, M. N. M., Kahar

    Published 2015
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