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Showing 21 - 40 results of 906 for search '(( elements method algorithm ) OR ((( data using algorithms ) OR ( based testing algorithm ))))', query time: 0.14s Refine Results
  1. 21

    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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  2. 22

    Power System Transient Stability Assessment Based on Machine Learning Algorithms and Grid Topology by Senyuk, Mihail

    Published 2023
    “…Algorithms were tested using the test power system IEEE39. …”
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  3. 23

    Empirical comparison of regression test selection algorithms by Mansour, Nashat

    Published 2001
    “…In this paper, we empirically compare five representative regression test selection algorithms, which include: Simulated Annealing, Reduction, Slicing, Dataflow, and Firewall algorithms. …”
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  4. 24

    Natural optimization algorithms for optimal regression testing by Mansour, Nashat

    Published 1997
    “…The algorithms are based on an integer programming problem formulation and the program's control-flow graph. …”
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    A comparative study of five regression testing algorithms by Mansour, N.

    Published 1997
    “…We compare five regression testing algorithms that include: slicing, incremental, firewall, genetic and simulated annealing algorithms. …”
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  8. 28

    Simulated Annealing and Genetic Algorithms for Optimal Regression Testing by Mansour, Nashat

    Published 1999
    “…The algorithms are based on an integer programming problem formulation and the program’s control flow graph. …”
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  9. 29

    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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  10. 30

    A Hybrid Deep Learning Model Using CNN and K-Mean Clustering for Energy Efficient Modelling in Mobile EdgeIoT by Dhananjay Bisen (19482454)

    Published 2023
    “…The proposed method, existing weighted clustering algorithm (WCA), and agent-based secure enhanced performance approach (AB-SEP) are tested over the network dataset. …”
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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. …”
  14. 34

    An incremental approach for test scheduling and synthesis using genetic algorithms by Harmanani, H.

    Published 2017
    “…The method is based on a genetic algorithm that efficiently explores the testable design space. …”
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  15. 35

    Concurrent BIST Synthesis and Test Scheduling Using Genetic Algorithms by Harmanani, H. M.

    Published 2007
    “…The method is based on a genetic algorithm that efficiently explores the testable design space and finds a sub-optimal test registers assignment for each k-test session. …”
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  16. 36

    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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    Limiting the Collection of Ground Truth Data for Land Use and Land Cover Maps with Machine Learning Algorithms by Usman Ali (6586886)

    Published 2022
    “…This was accomplished by (1) extracting reliable LULC information from Sentinel-2 and Landsat-8 s images, (2) generating remote sensing indices used to train ML algorithms, and (3) comparing the results with ground truth data. …”
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    Data reductions and combinatorial bounds for improved approximation algorithms by Abu-Khzam, Faisal N.

    Published 2016
    “…Kernelization algorithms in the context of Parameterized Complexity are often based on a combination of data reduction rules and combinatorial insights. …”
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