Search Results - (( using function clustering algorithm ) OR ( parallel implementation _ algorithm ))

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  1. 1

    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
  2. 2

    Enhancing speed performance of the cryptographic algorithm based on the lucas sequence by M. Abulkhirat, Esam

    Published 2003
    “…Reducing the calculation time of the algorithm, in sequential and parallel platforms, using the doubling-rule technique combined with a new scheme led to a strong improvement of the LUC algorithm speed. …”
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    Thesis
  3. 3

    Implementation of Parallel K-Means Algorithm to Estimate Adhesion Failure in Warm Mix Asphalt by Akhtar, M.N., Ahmed, W., Kakar, M.R., Bakar, E.A., Othman, A.R., Bueno, M.

    Published 2020
    “…The results showed that the PKIP algorithm decreases the execution time up to 30 to 46 if compared with the sequential k means algorithm when implemented using multiprocessing and distributed computing. …”
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    Article
  4. 4

    Determining the preprocessing clustering algorithm in radial basis function neural network by S.L. Ang, H.C. Ong, H.C. Law

    Published 2008
    “…Three types of method used in this study to find the centres include random selections, K-means clustering algorithm and also K-median clustering algorithm. …”
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    Article
  5. 5

    Biological-based semi-supervised clustering algorithm to improve gene function prediction by Kasim, Shahreen, Deris, Safaai, M. Othman, Razib, Hashim, Rathiah

    Published 2011
    “…However, commonclustering algorithms do not provide a comprehensive approach that look into the three categories of annotations; biologicalprocess, molecular function, and cellular component, and were not tested with different functional annotation database formats.Furthermore, the traditional clustering algorithms use random initialization which causes inconsistent cluster generation and areunable to determine the number of clusters involved. …”
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    Article
  6. 6

    Statistical data preprocessing methods in distance functions to enhance k-means clustering algorithm by Dalatu, Paul Inuwa

    Published 2018
    “…The K-Means algorithm is the commonest and fast technique in partitional cluster algorithms, although with unnormalized datasets it can achieve local optimal. …”
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    Thesis
  7. 7

    An Efficient Parallel Quarter-sweep Point Iterative Algorithm for Solving Poisson Equation on SMP Parallel Computer by M., Othman, A. R., Abdullah

    Published 2000
    “…However, the last two algorithms were found to be suitable for parallel implementation (Evans 1984) and Ali el at. (1997». …”
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    Article
  8. 8

    A permutation parallel algorithm under exchange restriction with message passing interface by Karim, Sharmila, Omar, Zurni, Ibrahim, Haslinda

    Published 2014
    “…The sequential algorithm is implemented to a parallel algorithm by integrating with Message Passing Interface (MPI) libraries by paralleling the starter sets generation task.The speedup and efficiency is the indicator tool for analyzing performance of this parallel algorithm.The results show reduction time computation of parallel algorithm among processors.…”
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    Conference or Workshop Item
  9. 9

    Parallelization of noise reduction algorithm for seismic data on a beowulf cluster by Aziz, I. A., Sandran, T., Haron, N. S., Hasan, M. H, Mehat, M.

    Published 2010
    “…This paper presents the parallelization of a sequential noise reduction algorithm for seismic data processing into a parallel algorithm. …”
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    Citation Index Journal
  10. 10
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    A soft hierarchical algorithm for the clustering of multiple bioactive chemical compounds by Salim, Naomie, Shah, J. Z.

    Published 2007
    “…In this work a fuzzy hierarchical algorithm is developed which provides a mechanism not only to benefit from the fuzzy clustering process but also to get advantage of the multiple membership function of the fuzzy clustering. …”
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    Book Section
  12. 12

    A review: accuracy optimization in clustering ensembles using genetic algorithms by Ghaemi, Reza, Sulaiman, Md. Nasir, Ibrahim, Hamidah, Mustapha, Norwati

    Published 2011
    “…This paper concludes that using genetic algorithms in clustering ensemble improves the clustering accuracy and addresses open questions subject to future research.…”
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    Article
  13. 13

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

    Published 2014
    “…A data parallel algorithm (DPA-EHD) is designed and implemented for the EHD equations. …”
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    Thesis
  14. 14

    Implementation of a parallel XTS encryption mode of operation by Alomari, Mohammad Ahmed, Samsudin, Khairulmizam, Ramli, Abdul Rahman

    Published 2014
    “…The parallel XTS algorithm has shown a speedup of 1.80, with 90% efficiency, faster than the sequential algorithm. …”
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    Article
  15. 15

    A fast, parallel performance of fourth order iterative algorithm on shared memory multiprocessors (SMP) architecture by Othman, Mohamed, Sulaiman, Jumat

    Published 2006
    “…In this paper, the implementation of the parallel rotated fourth order iterative algorithm on SMP architecture is discussed. …”
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    Conference or Workshop Item
  16. 16

    Parallel implementation on improved error signal of backpropagation algorithm by Mohd Aris, Teh Noranis

    Published 2001
    “…The experiments are implemented using the Sequent Symmetry SE30 parallel machine. …”
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    Thesis
  17. 17

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

    Published 2012
    “…Moreover, experiments demonstrate that final clustering solution generated by the proposed incremental genetic-based clustering ensemble algorithm using the pattern ensemble learning method possess comparative or better clustering accuracy than clustering solutions generated by the incremental genetic-based clustering ensemble algorithms using other recombination operators. …”
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    Thesis
  18. 18

    Parallel implementation on improved error signal of backpropagation algorithm by Mohd Aris, Teh Noranis, Sulaiman, Md. Nasir, Mohd Saman, Md. Yazid, Othman, Mohamed

    Published 2002
    “…Further study on the improved BP algorithm is carried out on many processors, which is implemented using the Sequent Symmetry SE30 machine. …”
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    Article
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  20. 20

    Indoor positioning using weighted magnetic field signal distance similarity measure and fuzzy based algorithms by Bundak, Caceja Elyca

    Published 2021
    “…Therefore, for the second objective, another algorithm named the fuzzy algorithm is designed which combines the clustering algorithm, matching algorithm, triangle area algorithm and average Euclidean algorithm used to estimate location. …”
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    Thesis