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Showing 1 - 20 results of 751 for search '(( elements method algorithm ) OR ((( data using algorithms ) OR ( based mapping algorithm ))))*', query time: 0.14s Refine Results
  1. 1

    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 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
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    A novel encryption algorithm using multiple semifield S-boxes based on permutation of symmetric group by Iqtadar Hussain (14147850)

    Published 2023
    “…The presented algorithm is mainly based on the Shannon idea of substitution–permutation network where the process of substitution is performed by the proposed S<sub>8</sub> semifield substitution boxes and permutation operation is performed by the binary cyclic shift of substitution box transformed data. …”
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    Stochastic evolution algorithm for technology mapping by Al-Mulhem, A.S.

    Published 1998
    “…SELF-Map is based on the Stochastic Evolution (SE) algorithm. …”
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    article
  7. 7

    Multi-marker-LD based genetic algorithm for tag SNP selection by Mansour, Nashat

    Published 2014
    “…The performance of the three algorithms are compared with those of a recognized tag SNP selection algorithm using three different real data sets from the HapMap project. …”
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    article
  8. 8

    Efficient Approximate Conformance Checking Using Trie Data Structures by Awad, Ahmed

    Published 2021
    “…By encoding the proxy behavior using a trie data structure, we obtain a logarithmically reduced search space for alignment computation compared to a set-based representation. …”
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  9. 9

    Comparative analysis of metaheuristic load balancing algorithms for efficient load balancing in cloud computing by Jincheng Zhou (1887307)

    Published 2023
    “…This paper provides a comparative analysis of various metaheuristic load balancing algorithms for cloud computing based on performance factors i.e., Makespan time, degree of imbalance, response time, data center processing time, flow time, and resource utilization. …”
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    Allocation and re-allocation of data in a grid using an adaptive genetic algorithm by Mansour, N.

    Published 2006
    “…Allocation and re-allocation of data in a grid using an adaptive genetic algorithm. …”
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    conferenceObject
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    Map-based mobile positioning system by Saab, S. S.

    Published 2002
    “…In this paper, a mobile positioning system (MPS) is proposed based on a map-matching algorithm. Using the triangulation or a trilateration technique, the Cell of Origin, Time of Arrival, and Time Difference of Arrival, the mobile is first located within a specified area of about 500x500 squared meters in a GSM network and within a specified area of about 244x244 squared meters in an IS-95 network. …”
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    article
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    Cryptocurrency Exchange Market Prediction and Analysis Using Data Mining and Artificial Intelligence by Al Rayhi, Nasser

    Published 2020
    “…One of the best algorithms in terms of the result is the Long Short Term Memory (LSTM) since it is based on recurrent neural networks which uses loop as a method to learn from heuristics data. …”
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    Variable Selection in Data Analysis: A Synthetic Data Toolkit by Mitra, Rohan

    Published 2024
    “…Variable (feature) selection plays an important role in data analysis and mathematical modeling. This paper aims to address the significant lack of formal evaluation benchmarks for feature selection algorithms (FSAs). …”
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    article
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    Using Machine Learning Algorithms to Forecast Solar Energy Power Output by Ali Jassim Lari (22597940)

    Published 2025
    “…We focused on the first 30-min, 3-h, 6-h, 12-h, and 24-h windows to gain an appreciation of the impact of forecasting duration on the accuracy of prediction using the selected machine learning algorithms. The study results show that Random Forest outperformed all other tested algorithms. …”
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    Predicting Dropouts among a Homogeneous Population using a Data Mining Approach by BILQUISE, GHAZALA

    Published 2019
    “…Our research relies solely on pre-college and college performance data available in the institutional database. Our research reveals that the Gradient Boosted Trees is a robust algorithm that predicts dropouts with an accuracy of 79.31% and AUC of 88.4% using only pre-enrollment data. …”
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