بدائل البحث:
process optimization » model optimization (توسيع البحث)
wolf optimization » whale optimization (توسيع البحث), swarm optimization (توسيع البحث), _ optimization (توسيع البحث)
based process » based processes (توسيع البحث), based probes (توسيع البحث), based proteins (توسيع البحث)
binary based » library based (توسيع البحث), linac based (توسيع البحث), binary mask (توسيع البحث)
lines based » lens based (توسيع البحث), genes based (توسيع البحث), lines used (توسيع البحث)
based wolf » based whole (توسيع البحث), based work (توسيع البحث), based well (توسيع البحث)
process optimization » model optimization (توسيع البحث)
wolf optimization » whale optimization (توسيع البحث), swarm optimization (توسيع البحث), _ optimization (توسيع البحث)
based process » based processes (توسيع البحث), based probes (توسيع البحث), based proteins (توسيع البحث)
binary based » library based (توسيع البحث), linac based (توسيع البحث), binary mask (توسيع البحث)
lines based » lens based (توسيع البحث), genes based (توسيع البحث), lines used (توسيع البحث)
based wolf » based whole (توسيع البحث), based work (توسيع البحث), based well (توسيع البحث)
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An Example of a WPT-MEC Network.
منشور في 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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Related Work Summary.
منشور في 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.
منشور في 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.
منشور في 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.
منشور في 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.
منشور في 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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Performance on GradEva.
منشور في 2024"…The sequences generated by our algorithm identify points that satisfy the first-order necessary condition for Pareto optimality. …"
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The considered test problems.
منشور في 2024"…The sequences generated by our algorithm identify points that satisfy the first-order necessary condition for Pareto optimality. …"
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Performance on FunEva.
منشور في 2024"…The sequences generated by our algorithm identify points that satisfy the first-order necessary condition for Pareto optimality. …"
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Performance on Iter.
منشور في 2024"…The sequences generated by our algorithm identify points that satisfy the first-order necessary condition for Pareto optimality. …"
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Continuation of Table 2.
منشور في 2024"…The sequences generated by our algorithm identify points that satisfy the first-order necessary condition for Pareto optimality. …"
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Improved support vector machine classification algorithm based on adaptive feature weight updating in the Hadoop cluster environment
منشور في 2019"…<div><p>An image classification algorithm based on adaptive feature weight updating is proposed to address the low classification accuracy of the current single-feature classification algorithms and simple multifeature fusion algorithms. …"
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Design and implementation of the Multiple Criteria Decision Making (MCDM) algorithm for predicting the severity of COVID-19.
منشور في 2021"…<p>(A). The MCDM algorithm-Stage 1. Preprocessing, this stage is the process of refining the collected raw data to eliminate noise, including correlation analysis and feature selection based on P values. …"
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Parameter settings.
منشور في 2024"…<div><p>Differential Evolution (DE) is widely recognized as a highly effective evolutionary algorithm for global optimization. It has proven its efficacy in tackling diverse problems across various fields and real-world applications. …"
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GSE96058 information.
منشور في 2024"…Subsequently, feature selection was conducted using ANOVA and binary Particle Swarm Optimization (PSO). During the analysis phase, the discriminative power of the selected features was evaluated using machine learning classification algorithms. …"