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Showing 21 - 40 results of 275 for search '(((( data mining algorithm ) OR ( based finding algorithm ))) OR ( element method algorithm ))*', query time: 0.12s Refine Results
  1. 21

    Orthogonal Learning Rosenbrock’s Direct Rotation with the Gazelle Optimization Algorithm for Global Optimization by Abu Zitar, Raed

    Published 2022
    “…An efficient optimization method is needed to address complicated problems and find optimal solutions. The gazelle optimization algorithm (GOA) is a global stochastic optimizer that is straightforward to comprehend and has powerful search capabilities. …”
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  2. 22

    Application of updated joint detection algorithm for the analysis of drilling parameters of roof bolters in multiple joints conditions by Liu, Wenpeng

    Published 2017
    “…This paper reviews testing procedures, data analysis, updated algorithms used for joint detection, and discusses the latest round of testing in samples with simulated joints at various angles along the borehole.…”
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    Using Educational Data Mining Techniques in Predicting Grade-4 students’ performance in TIMSS International Assessments in the UAE by SHWEDEH, FATEN

    Published 2018
    “…Classification is a Data Mining (DM) technique used for prediction. On the other hand, feature selection is the process of finding the best set of features that has the most impact on a specific target. …”
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    Use data Mining Techniques to Predict Users’ Engagement on the Social Network Posts in The Period Before, During and After Ramadan by AL RAWASHDEH, HANEEN MOHAMMAD

    Published 2017
    “…In this thesis, the effectiveness of using a data mining classifier helps to predict users’ engagement with a social media post before publishing and anticipating the best type of media for the post. …”
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    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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    BioNetApp: An interactive visual data analysis platform for molecular expressions by Ali M. Roumani (18615124)

    Published 2019
    “…BioNetApp also provides data clustering based on molecular concentrations using Self Organizing Maps (SOM), K-Means, K-Medoids, and Farthest First algorithms.…”
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    Application of Red Deer Algorithm in Optimizing Complex functions by Zitar, Raed

    Published 2021
    “…The Red Deer algorithm (RDA), a recently developed population-based meta-heuristic algorithm, is examined in this paper with the optimization task of complex functions. …”
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    Process Mining over Unordered Event Streams by Awad, Ahmed

    Published 2020
    “…This requires online algorithms that, instead of keeping the whole history of event data, work incrementally and update analysis results upon the arrival of new events. …”
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  17. 37

    A matrix-based damage assessment and recovery algorithm by Haraty, Ramzi A.

    Published 2014
    “…To make the process of damage assessment and recovery fast and effective (not scanning the entire log), researchers have proposed different methods for segmenting the log file, and accordingly presented different damage assessment and recovery algorithms. In this work we present efficient damage assessment and recovery algorithms to recover from malicious transactions in a database based on the concept of the matrix. …”
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  18. 38

    A reduced model for phase-change problems with radiation using simplified PN approximations by Belhamadia, Youssef

    Published 2025
    “…The integro-differential equation for the full radiative transfer is replaced by a set of differential equations which are independent of the angle variable and easy to solve using conventional computational methods. To solve the coupled equations, we implement a second-order implicit scheme for the time integration and a mixed finite element method for the space discretization. …”
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    article
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    UniBFS: A novel uniform-solution-driven binary feature selection algorithm for high-dimensional data by Behrouz Ahadzadeh (19757022)

    Published 2024
    “…<p>Feature selection (FS) is a crucial technique in machine learning and data mining, serving a variety of purposes such as simplifying model construction, facilitating knowledge discovery, improving computational efficiency, and reducing memory consumption. …”