Search Results - parallel computing ((best algorithm) OR (bee algorithm))*

Refine Results
  1. 1

    Performance Comparison of Parallel Bees Algorithm on Rosenbrock Function by Hammash, Nayif Mohammed

    Published 2012
    “…This thesis presents the parallel Bees Algorithm as a new approach for optimizing the last results for the Bees Algorithm. …”
    Get full text
    Get full text
    Get full text
    Thesis
  2. 2

    Efficient Sequential and Parallel Routing Algorithms in Optical Multistage Interconnection Network by Abduh Kaid, Monir Abdullah

    Published 2005
    “…The efficient combination of simulated annealing algorithm with the best heuristic algorithms gave much better result in a very minimal time. …”
    Get full text
    Get full text
    Thesis
  3. 3
  4. 4

    Energy-aware scheduling optimization in hybrid flow shops using artificial bee colony algorithm by Mohd Abdul Hadi, Osman, Mohd Fadzil Faisae, Ab Rashid, Nik Mohd Zuki, Nik Mohamed, Muhammad Ammar, Nik Mu’tasim

    Published 2024
    “…Through an extensive computational experiment involving a well-known benchmark suite, the ABC algorithm demonstrated remarkable performance, consistently outperforming several popular metaheuristic algorithms, including Genetic Algorithms, Particle Swarm Optimization, Memetic Algorithms, and Whale Optimization Algorithm in 75% of the problems. …”
    Get full text
    Get full text
    Get full text
    Article
  5. 5

    Parallel batch self-organizing map on graphics processing unit using CUDA by Daneshpajouh, H., Delisle, P., Boisson, J.-C., Krajecki, M., Zakaria, N.

    Published 2018
    “…The most computationally expensive parts of its training algorithm (such as steps to compute distance between each data vector and neuron, and determining the Best Matching Unit based on minimum distance) are identified and mapped on GPU to be processed in parallel. …”
    Get full text
    Get full text
    Article
  6. 6

    Parallel batch self-organizing map on graphics processing unit using CUDA by Daneshpajouh, H., Delisle, P., Boisson, J.-C., Krajecki, M., Zakaria, N.

    Published 2018
    “…The most computationally expensive parts of its training algorithm (such as steps to compute distance between each data vector and neuron, and determining the Best Matching Unit based on minimum distance) are identified and mapped on GPU to be processed in parallel. …”
    Get full text
    Get full text
    Article
  7. 7

    Accelerating DNA sequence alignment based on smith waterman algorithm using recursive variable expansion / Muhamad Faiz Ismail by Ismail, Muhamad Faiz

    Published 2014
    “…Reconfigurable computing, in which general purpose processor (GPP) is increasingly used for high performance computing where massive fine-grain parallelism can be exploited. …”
    Get full text
    Get full text
    Thesis
  8. 8

    A Parallel-Model Speech Emotion Recognition Network Based on Feature Clustering by Li-Min Zhang, Giap Weng Ng, Yu-Beng Leau, Hao Yan

    Published 2023
    “…To address this issue, we proposed a novel algorithm called F-Emotion to select speech emotion features and established a parallel deep learning model to recognize different types of emotions. …”
    Get full text
    Get full text
    Get full text
    Get full text
    Article
  9. 9

    A parallel-model speech emotion recognition network based on feature clustering by Li-Min Zhang, Giap Weng Ng, Yu-Beng Leau, Hao Yan

    Published 2023
    “…To address this issue, we proposed a novel algorithm called F-Emotion to select speech emotion features and established a parallel deep learning model to recognize different types of emotions. …”
    Get full text
    Get full text
    Get full text
    Article
  10. 10

    Parallelizing GF (p) montgomery elliptic curve crypto-system operations to improve security and performance. by Mohammad Alkhatib, Jaafar, Azmi, Md Said, Mohamad Rushdan, Ahmad Zukarnain, Zuriati

    Published 2012
    “…Hardware implementations with target FPGA for GF (p) Montgomery ECC are also presented. The best performance level was achieved when parallelizing Montgomery ECC computations to eight parallel multipliers (PM) using homogeneous coordinates. …”
    Get full text
    Get full text
    Get full text
    Conference or Workshop Item
  11. 11

    Parallelizing GF (p) montgomery elliptic curve crypto-system operations to improve security and performance. by Alkhatib, Mohammad, Jaafar, Azmi, Md Said, Mohamad Rushdan, Ahmad Zulkarnain, Zuriati

    Published 2013
    “…Hardware implementations with target FPGA for GF (p) Montgomery ECC are also presented. The best performance level was achieved when parallelizing Montgomery ECC computations to eight parallel multipliers (PM) using homogeneous coordinates. …”
    Get full text
    Get full text
    Book Section
  12. 12
  13. 13
  14. 14
  15. 15
  16. 16
  17. 17

    Protein secondary structure prediction from amino acid sequences using a neural network classifier based on the Dempster-Shafer theory by Vel Arjunan, Satya Nanda

    Published 2003
    “…In order to reduce the computational demand when training with large data of proteins, an interface was developed using the data parallel approach to parallelize the training phase of the classifier and other accompanying methods such as data clustering algorithms. …”
    Get full text
    Get full text
    Thesis
  18. 18
  19. 19
  20. 20

    New methods of partial transmit sequence for reducing the high peak-to-average-power ratio with low complexity in the ofdm and f-ofdm systems by Abduljabbar, Yasir Amer

    Published 2019
    “…Based on the proposed methods, an improved PTS method that merges the best subblock partitioning scheme in the frequency domain and the best low-complexity algorithm in the time domain has been introduced to enhance the PAPR reduction performance better than the conventional PTS method with extremely low computational complexity level. …”
    Get full text
    Get full text
    Get full text
    Get full text
    Thesis