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Showing 361 - 367 results of 367 for search '(((( case finding algorithm ) OR ( data processing algorithm ))) OR ( element means algorithm ))', query time: 0.09s Refine Results
  1. 361

    Using artificial bee colony to optimize software quality estimation models. (c2015) by Abou Assi, Tatiana Antoine

    Published 2016
    “…We validate our technique on data describing maintainability and reliability of classes in an Object-Oriented system. …”
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    masterThesis
  2. 362

    From Collatz Conjecture to chaos and hash function by Masrat Rasool (17807813)

    Published 2023
    “…The effectiveness and dependability of the proposed hash function are evaluated by comparing it with two well-known hash algorithms, namely SHA-3 and SHA-2, as well as several other Chaos-based hash algorithms. …”
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    Semantics-based approach for detecting flaws, conflicts and redundancies in XACML policies by Jebbaoui, Hussein

    Published 2015
    “…First, our approach resolves the complexity of policies by elaborating an intermediate set-based representation to which the elements of XACML are automatically converted. Second, it allows to detect flaws, conflicts and redundancies between rules by offering new mechanisms to analyze the meaning of policy rules through semantics verification by inference rule structure and deductive logic. …”
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    article
  6. 366

    An enhanced binary Rat Swarm Optimizer based on local-best concepts of PSO and collaborative crossover operators for feature selection by Abu Zitar, Raed

    Published 2022
    “…Many FS-based swarm intelligence algorithms have been used to tackle FS. However, the door is still open for further investigations since no FS method gives cutting-edge results for all cases. …”
  7. 367

    Predictive modelling in times of public health emergencies: patients’ non-transport decisions during the COVID-19 pandemic by Hassan Farhat (9000509)

    Published 2025
    “…</p><h3>Results</h3><p dir="ltr">From June 2018 to July 2022, 334,392 non-transport cases were recorded. The random forest model demonstrated the best optimised predictive performance, with accuracy = 74.78%, F1 = 0.74, MCC = 0.35, ROC AUC = 0.81, kappa = 0.34, and R-squared = 0.81. …”