Showing 41 - 60 results of 744 for search '(( data using algorithm ) OR ((( develop search algorithm ) OR ( relevant data algorithm ))))', query time: 0.16s Refine Results
  1. 41

    Methodology for Analyzing the Traditional Algorithms Performance of User Reviews Using Machine Learning Techniques by Abdul Karim (417009)

    Published 2020
    “…This conclusion was achieved after preprocessing a number of data values from these data sets.</p><h2>Other Information</h2><p dir="ltr">Published in: Algorithms<br>License: <a href="https://creativecommons.org/licenses/by/4.0/" target="_blank">https://creativecommons.org/licenses/by/4.0/</a><br>See article on publisher's website: <a href="https://dx.doi.org/10.3390/a13080202" target="_blank">https://dx.doi.org/10.3390/a13080202</a></p>…”
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    Web Based Online Hybrid Teaching Method of Network Music Course by Abu Zitar, Raed

    Published 2022
    “…Based on Web data mining, an improved algorithm of hybrid hierarchical recommendation algorithm and genetic algorithm is used in the experiment, and compared with the other two algorithms in the experiment. …”
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  5. 45

    Properties of simulated annealing and genetic algorithms for mapping data to multicomputers by Mansour, Nashat

    Published 1997
    “…Some user parameters are included in the objective function and are architecture- or problem-dependent parameters. The others are used in the GA and SA algorithms. The fault tolerance capability is demonstrated by mapping data to a multicomputer with some faulty processors. …”
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    article
  6. 46

    Physical optimization algorithms for mapping data to distributed-memory multiprocessors by Mansour, Nashat

    Published 1992
    “…We present three parallel physical optimization algorithms for mapping data to distributed-memory multiprocessors, concentrating on irregular loosely synchronous problems. …”
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    masterThesis
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    A Genetic Algorithm for Improving Accuracy of Software Quality Predictive Models by Azar, Danielle

    Published 2010
    “…In this work, we present a genetic algorithm to optimize predictive models used to estimate software quality characteristics. …”
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    article
  9. 49

    Novel Peak Detection Algorithms for Pileup Minimization in Gamma Ray Spectroscopy by Raad, M.W.

    Published 2006
    “…A number of parameter estimation and digital online peak localisation algorithms are being developed, including a pulse classification technique which uses a simple peak search routine based on the smoothed first derivative method, which gave a percentage error of peak amplitude of less than 1%. …”
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    article
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    A comparison of data mapping algorithms for parallel iterative PDE solvers by Mansour, Nashat

    Published 1995
    “…We review and evaluate the performances of six data mapping algorithms used for parallel single-phase iterative PDE solvers with irregular 2-dimensional meshes on multicomputers. …”
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    article
  14. 54

    An enhanced k-means clustering algorithm for pattern discovery in healthcare data by Haraty, Ramzi A.

    Published 2015
    “…This paper studies data mining applications in healthcare. Mainly, we study k-means clustering algorithms on large datasets and present an enhancement to k-means clustering, which requires k or a lesser number of passes to a dataset. …”
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    article
  15. 55

    Efficient Dynamic Cost Scheduling Algorithm for Financial Data Supply Chain by Al Sadawi, Alia

    Published 2021
    “…The primary tool used in the data supply chain is data batch processing which requires efficient scheduling. …”
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    article
  16. 56

    DG-Means – A Superior Greedy Algorithm for Clustering Distributed Data by Assaf, Ali

    Published 2022
    “…In this work, we present DG-means, which is a greedy algorithm that performs on distributed sets of data. …”
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    masterThesis
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    Improvement of Kernel Principal Component Analysis-Based Approach for Nonlinear Process Monitoring by Data Set Size Reduction Using Class Interval by Mohammed Tahar Habib Kaib (21633176)

    Published 2024
    “…In this paper, the proposed algorithm selects relevant observations from the original data set by utilizing a class interval technique (i.e. histogram) to maintain a bunch of representative samples from each bin. …”