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processing algorithm » modeling algorithm (Expand Search), routing algorithm (Expand Search), tracking algorithm (Expand Search)
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data algorithm » data algorithms (Expand Search), update algorithm (Expand Search), atlas algorithm (Expand Search)
element data » settlement data (Expand Search), relevant data (Expand Search), movement data (Expand Search)
processing algorithm » modeling algorithm (Expand Search), routing algorithm (Expand Search), tracking algorithm (Expand Search)
learning algorithm » learning algorithms (Expand Search)
data processing » image processing (Expand Search)
solved learning » novel learning (Expand Search), involve learning (Expand Search), applied learning (Expand Search)
data algorithm » data algorithms (Expand Search), update algorithm (Expand Search), atlas algorithm (Expand Search)
element data » settlement data (Expand Search), relevant data (Expand Search), movement data (Expand Search)
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Comparison of different optimization algorithms.
Published 2025Subjects: “…crayfish optimization algorithm…”
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Training process of HFKG-RFE algorithm.
Published 2025“…Therefore, An Algorithm for Heterogeneous Federated Knowledge Graph (HFKG) is proposed to solve this problem by limiting model drift through comparative learning. …”
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The run time for each algorithm in seconds.
Published 2025“…The goal of this paper is to examine several extensions to KGR/GPoG, with the aim of generalising them a wider variety of data scenarios. The first extension we consider is the case of graph signals that have only been partially recorded, meaning a subset of their elements is missing at observation time. …”
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Schematic diagram of the experimental algorithm.
Published 2025“…Second, the egg carrier structure is designed, the material properties are analysed, and key parameters such as deformation are simulated by SolidWorks and Ansys Workbench. Finite element and fatigue analyses are carried out for the key parameters of the structure, and deformation, fatigue and other data that appear in the actual operation process are obtained. …”
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Proposed Algorithm.
Published 2025“…EHRL integrates Reinforcement Learning (RL) with Deep Neural Networks (DNNs) to dynamically optimize binary offloading decisions, which in turn obviates the requirement for manually labeled training data and thus avoids the need for solving complex optimization problems repeatedly. …”
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