Showing 1 - 20 results of 196 for search '(( binary a based optimization algorithm ) OR ( binary based process maximization algorithm ))*', query time: 0.65s Refine Results
  1. 1

    Proposed Algorithm. by Hend Bayoumi (22693738)

    Published 2025
    “…To enhance the offloading decision-making process, the algorithm incorporates the Newton-Raphson method for fast and efficient optimization of the computation rate under energy constraints. …”
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    Comparisons between ADAM and NADAM optimizers. by Hend Bayoumi (22693738)

    Published 2025
    “…To enhance the offloading decision-making process, the algorithm incorporates the Newton-Raphson method for fast and efficient optimization of the computation rate under energy constraints. …”
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    An Example of a WPT-MEC Network. by Hend Bayoumi (22693738)

    Published 2025
    “…To enhance the offloading decision-making process, the algorithm incorporates the Newton-Raphson method for fast and efficient optimization of the computation rate under energy constraints. …”
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    MSE for ILSTM algorithm in binary classification. by Asmaa Ahmed Awad (16726315)

    Published 2023
    “…The ILSTM was then used to build an efficient intrusion detection system for binary and multi-class classification cases. The proposed algorithm has two phases: phase one involves training a conventional LSTM network to get initial weights, and phase two involves using the hybrid swarm algorithms, CBOA and PSO, to optimize the weights of LSTM to improve the accuracy. …”
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    Related Work Summary. by Hend Bayoumi (22693738)

    Published 2025
    “…To enhance the offloading decision-making process, the algorithm incorporates the Newton-Raphson method for fast and efficient optimization of the computation rate under energy constraints. …”
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    Simulation parameters. by Hend Bayoumi (22693738)

    Published 2025
    “…To enhance the offloading decision-making process, the algorithm incorporates the Newton-Raphson method for fast and efficient optimization of the computation rate under energy constraints. …”
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    Training losses for N = 10. by Hend Bayoumi (22693738)

    Published 2025
    “…To enhance the offloading decision-making process, the algorithm incorporates the Newton-Raphson method for fast and efficient optimization of the computation rate under energy constraints. …”
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    Normalized computation rate for N = 10. by Hend Bayoumi (22693738)

    Published 2025
    “…To enhance the offloading decision-making process, the algorithm incorporates the Newton-Raphson method for fast and efficient optimization of the computation rate under energy constraints. …”
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    Summary of Notations Used in this paper. by Hend Bayoumi (22693738)

    Published 2025
    “…To enhance the offloading decision-making process, the algorithm incorporates the Newton-Raphson method for fast and efficient optimization of the computation rate under energy constraints. …”
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    DE algorithm flow. by Ling Zhao (111365)

    Published 2025
    “…<div><p>To solve the problems of insufficient global optimization ability and easy loss of population diversity in building interior layout design, this study proposes a novel layout optimization model integrating interactive genetic algorithm and improved differential evolutionary algorithm to improve the global optimization ability and maintain population diversity in building layout design. …”
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    Test results of different algorithms. by Ling Zhao (111365)

    Published 2025
    “…<div><p>To solve the problems of insufficient global optimization ability and easy loss of population diversity in building interior layout design, this study proposes a novel layout optimization model integrating interactive genetic algorithm and improved differential evolutionary algorithm to improve the global optimization ability and maintain population diversity in building layout design. …”
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    Python-Based Algorithm for Estimating NRTL Model Parameters with UNIFAC Model Simulation Results by Se-Hee Jo (20554623)

    Published 2025
    “…A Python-based algorithm was developed for estimating the nonrandom two-liquid (NRTL) model parameters of aqueous binary systems in a straightforward manner from simplified molecular-input line-entry specification (SMILES) strings of substances in a system. …”
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    Algorithm for generating hyperparameter. by Balraj Preet Kaur (20370832)

    Published 2024
    “…Motivated by the above, in this proposal, we design an improved model to predict the existence of respiratory disease among patients by incorporating hyperparameter optimization and feature selection. To optimize the parameters of the machine learning algorithms, hyperparameter optimization with a genetic algorithm is proposed and to reduce the size of the feature set, feature selection is performed using binary grey wolf optimization algorithm. …”
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    datasheet1_Graph Neural Networks for Maximum Constraint Satisfaction.pdf by Jan Tönshoff (10192709)

    Published 2021
    “…We introduce a graph neural network architecture for solving such optimization problems. …”
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    Results of machine learning algorithm. by Balraj Preet Kaur (20370832)

    Published 2024
    “…Motivated by the above, in this proposal, we design an improved model to predict the existence of respiratory disease among patients by incorporating hyperparameter optimization and feature selection. To optimize the parameters of the machine learning algorithms, hyperparameter optimization with a genetic algorithm is proposed and to reduce the size of the feature set, feature selection is performed using binary grey wolf optimization algorithm. …”
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