Search Results - (( parallel evaluation method algorithm ) OR ( probable distribution selection algorithm ))*

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  1. 1

    Parallel Execution of Runge-Kutta Methods for Solving Ordinary Differential Equations by Siri, Zailan

    Published 2004
    “…The method used here is actually have been tailored made for the purpose of parallel machine where the subsequent functions evaluations do not depend on the previous function evaluations. …”
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    Thesis
  2. 2

    Statistical selection algorithm for peer-to-peer system by Othman, Mohamed, Kweh, Yeah Lun

    Published 2008
    “…Over the years, the distributed database has been developed so fast that there's a need to develop an effective selection algorithm for it. …”
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    Article
  3. 3

    Parallel algorithms for numerical simulations of EHD ion-drag micropump on distributed parallel computing systems by Shakeel Ahmed, Kamboh

    Published 2014
    “…To implement the parallel algorithms a distributed parallel computing laboratory using easily available low cost computers is setup. …”
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  4. 4

    Enhancing performance of XTS cryptography mode of operation using parallel design by Ahmed Alomari, Mohammad

    Published 2009
    “…In addition, the parallel XTS mode was also simulated using Twofish and RC6 encryption algorithms. …”
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  5. 5

    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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    Article
  6. 6

    Communication and computational cost on parallel algorithm of PDE elliptic type by Alias, Norma

    Published 2009
    “…Due to this needs, this paper presents the parallel performance evaluations of algorithms that will be discussed in term of communication and computational cost.…”
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    Book Section
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  8. 8

    Analysis of evolutionary computing performance via mapreduce parallel processing architecture / Ahmad Firdaus Ahmad Fadzil by Ahmad, Ahmad Firdaus

    Published 2014
    “…MR is an emerging parallel processing framework that hides the complex parallelization processes by employing the functional abstraction of "map and reduce" The Performance of the parallelized GA via MR and PSO via MR are evaluated using an analogous case study to find out the speedup and efficiency in order to measure the scalability of both proposed algorithms. …”
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  9. 9

    Fault section detection and location on distribution network using analytical voltage sags database by Khalid, A.R., Mokhlis, Hazlie, Li, H.

    Published 2006
    “…By doing this all the possible sections due to the fault can be selected. Finally, the most probable faulty section is identified using probability approach.This paper presents the implemented algorithms and the test of the algorithms on typical distribution networks. …”
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    Conference or Workshop Item
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    Enhanced Q-Learning algorithm for potential actions selection in automated graphical user interface testing by Goh, Kwang Yi

    Published 2023
    “…The idea was to change the probability distribution over the sequence space. Instead of making purely random selections, the least frequently executed action is selected so that the GUI can be further explored. …”
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  12. 12
  13. 13

    Improvement and performance analysis on statistical selection algorithms by Kweh, Yeah Lun, Othman, Mohamed

    Published 2006
    “…Over the years, the distributed database has been developed so fast that there's a need to develop an effective selection algorithm for it. …”
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    Conference or Workshop Item
  14. 14
  15. 15

    The Parallel Fuzzy C-Median Clustering Algorithm Using Spark for the Big Data by Mallik, Moksud Alam, Zulkurnain, Nurul Fariza, Siddiqui, Sumrana, Sarkar, Rashel

    Published 2024
    “…Therefore, we develop a Parallel Fuzzy C-Median Clustering Algorithm Using Spark for Big Data that can handle large datasets while maintaining high accuracy and scalability. …”
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    Article
  16. 16

    Sequential and parallel multiple tabu search algorithm for multiobjective urban transit scheduling problems by Uvaraja, Vikneswary

    Published 2018
    “…Additionally, the MTS algorithm is also implemented in parallel computing to produce parallel MTS for generating comparable solutions in shorter computational times. …”
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  17. 17

    Improving parallel self-organizing map using heterogeneous uniform memory access / Muhammad Firdaus Mustapha by Mustapha, Muhammad Firdaus

    Published 2018
    “…Finally, this research designs and implements an enhanced parallel SOM architecture through combining two parallel methods which are network and data partitioning. …”
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  18. 18

    A spark-based parallel fuzzy C median algorithm for web log big data by Mallik, Moksud Alam, Zulkurnain, Nurul Fariza, Nizamuddin, Mohammed Khaja, Sarkar, Rashal, Chalil, Aboosalih Kakkat

    Published 2022
    “…Based on the Rand Index and SSE (sum of squared error), the parallel Fuzzy C median algorithm's performance is evaluated in the PySpark platform. …”
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    Article
  19. 19

    Improving the exploration strategy of an automated android GUI testing tool based on the Q-Learning algorithm by selecting potential actions by Goh, Kwang Yi, Baharom, Salmi, Din, Jamilah

    Published 2022
    “…The idea was to change the probability distribution over the sequence space. Instead of making purely random selections, the least frequently executed action is selected so that the GUI can be further explored. …”
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    Article
  20. 20

    Fair bandwidth distribution marking and scheduling algorithm in network traffic classification by Al-Kharasani, Ameen Mohammed Abdulkarem

    Published 2019
    “…Additionally, the traffic are relying on the markers and scheduling algorithms to the service classes at the routers. The higher level priority agreements give a higher or equal probability than the lower level, this technique is perfect at a core router by scheduling algorithm. …”
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    Thesis