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Showing 81 - 100 results of 232 for search 'algorithms ((based function) OR (taste function))', query time: 0.08s Refine Results
  1. 81
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    Optimum sensors allocation for drones multi-target tracking under complex environment using improved prairie dog optimization by Abu Zitar, Raed

    Published 2024
    “…The goal is to select a set of sensors based on norms of weighted distances cost function. …”
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  3. 83

    A hybridization of evolution strategies with iterated greedy algorithm for no-wait flow shop scheduling problems by Bilal Khurshid (16715865)

    Published 2024
    “…<p dir="ltr">This study investigates the no-wait flow shop scheduling problem and proposes a hybrid (HES-IG) algorithm that utilizes makespan as the objective function. …”
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    Optimized Load-Scheduling Algorithm for CubeSat's Electric Power System Management Considering Communication Link by Bayan Hussein (16904856)

    Published 2023
    “…An optimization problem is formulated with data rate and BER in the cost function while maintaining energy and power constraints. …”
  8. 88

    Improved Dwarf Mongoose Optimization for Constrained Engineering Design Problems by Agushaka, Jeffrey O.

    Published 2022
    “…This optimization technique modifies the base algorithm (DMO) in three simple but effective ways. …”
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  9. 89

    Axes-Based Encryption Key by Haidar, Imane

    Published 2018
    “…This paper introduces a new approach in cryptography based on the distribution of data using an x-y key function. …”
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    conferenceObject
  10. 90
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    An efficient failure-resilient mutual exclusion algorithm for distributed systems leveraging a novel zero-message overlay structure by Mouna Rabhi (17086969)

    Published 2024
    “…<p>In this paper, we provide a novel failure-resilient token-based mutual exclusion (ME) algorithm for distributed systems. …”
  13. 93

    IoT-Based Sustainable Parking Lot by Binmahfooz, Abdullah

    Published 2023
    “…Experimental results showed that the system was able to perform the functionality with high accuracy. The coefficient of determination (R²) achieved of the car congestion prediction module was 0.97. …”
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    article
  14. 94
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    Fragment-based computational protein structure prediction by Mansour, Nashat

    Published 2014
    “…The method is based on a two-phase Scatter Search algorithm that minimizes the energy function. …”
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    conferenceObject
  16. 96

    Minimizing using BBO and DFO methods by El Zeghondy, Jean

    Published 2022
    “…In order to apply this algorithm to real life problems, two numerical methods need to be developed: A numerical method to solve nonlinear differential equations, and a numerical method to nd the minimum of an objective function (given only numerically) in fi nite dimensional spaces. …”
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    masterThesis
  17. 97

    Boosting the visibility of services in microservice architecture by Ahmet Vedat Tokmak (17773479)

    Published 2023
    “…These assessments can be performed by means of a live health-check service, or, alternatively, by making a prediction of the current state of affairs with the application of machine learning-based approaches. In this research, we evaluate the performance of several classification algorithms for estimating the quality of microservices using the QWS dataset containing traffic data of 2505 microservices. …”
  18. 98

    Upgraded SemIndex Prototype Supporting Intelligent Database Keyword Queries through Disambiguation, Query as You Type, and Parallel Search Algorithms by Tekli, Joe

    Published 2018
    “…Here, we build on top of SemIndex, a semantic-aware inverted index previously developed by our team, to allow semantic-aware search, result selection, and result ranking functionality. Various weighting functions and intelligent search algorithms have been developed for that purpose and will be presented here. …”
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    conferenceObject
  19. 99
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    ANT-colony optimization-direct torque control for a doubly fed induction motor : An experimental validation by Said Mahfoud (17150968)

    Published 2022
    “…The best solutions adopted in this situation are often based on optimization algorithms that generate the controller’s gains in each period where there is an internal or external perturbation, adapting the behaviors of the PID against the system’s nonlinearity. …”