Search Results - parallel evaluation ((mining algorithm) OR (means algorithm))

  • Showing 1 - 11 results of 11
Refine Results
  1. 1

    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. …”
    Get full text
    Get full text
    Get full text
    Get full text
    Article
  2. 2

    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. …”
    Get full text
    Get full text
    Get full text
    Get full text
    Article
  3. 3
  4. 4

    Online system identification development based on recursive weighted least square neural networks of nonlinear hammerstein and wiener models. by Kwad, Ayad Mahmood

    Published 2022
    “…The goodness of fit validation based on the normalized root-mean-square error (NRMSE) and normalized mean square error, and Theil’s inequality coefficient are used to evaluate the performance of models. …”
    Get full text
    Get full text
    Get full text
    Get full text
    Thesis
  5. 5

    Autonomous anomaly detection using density-based features in streaming data / Muhammmad Yunus Iqbal Basheer by Iqbal Basheer, Muhammmad Yunus

    Published 2023
    “…The proposed algorithms were evaluated to test their speed in handling streaming data. …”
    Get full text
    Get full text
    Thesis
  6. 6

    Random sampling method of large-scale graph data classification by Rashed Mustafa, Mohammad Sultan Mahmud, Mahir Shadid

    Published 2024
    “…Since the data blocks in this model are much smaller than the entire data set, it is more efficient to analyze them on a standalone small machine, and multiple data blocks can be analyzed on multiple nodes of the cluster in parallel. Finally, we classified the graphs of data blocks using the SVM algorithm. …”
    Get full text
    Get full text
    Get full text
    Article
  7. 7
  8. 8

    Improved criteria determination of an automated negative lightning return strokes characterisation using Brute-Force search algorithm by Abdul Haris, Faranadia

    Published 2021
    “…A total of 206 negative lightning return strokes waveforms were analysed and automatically characterised using the proposed algorithm. Comparisons of different data, including the manual data (i.e. obtained through the conventional method), data (automated) from a previous study, and the automated data (i.e. obtained using the proposed algorithm), were also carried out by evaluating the percentage difference, arithmetic mean, and standard deviation. …”
    Get full text
    Get full text
    Thesis
  9. 9
  10. 10

    Authenticating sensitive diacritical texts using residual, data representation and pattern matching methods / Saqib Iqbal Hakak by Saqib Iqbal , Hakak

    Published 2018
    “…The searching of halves is achieved through two different algorithms based on the split approach and the parallel approach respectively. …”
    Get full text
    Get full text
    Get full text
    Thesis
  11. 11

    Online teleoperation of writing manipulator through graphics processing unit based accelerated stereo vision by Abu Raid, Fadi Imad Osman

    Published 2021
    “…These algorithms are then parallelized using Compute Unified Device Architecture CUDA C language to run on Graphics Processing Unit GPU for hardware acceleration. …”
    Get full text
    Get full text
    Thesis