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method algorithm » network algorithm (Expand Search), means algorithm (Expand Search), mean algorithm (Expand Search)
making algorithm » learning algorithm (Expand Search), finding algorithm (Expand Search), means algorithm (Expand Search)
elements method » element method (Expand Search)
data modeling » data modelling (Expand Search), data models (Expand Search)
solved making » solved using (Expand Search)
method algorithm » network algorithm (Expand Search), means algorithm (Expand Search), mean algorithm (Expand Search)
making algorithm » learning algorithm (Expand Search), finding algorithm (Expand Search), means algorithm (Expand Search)
elements method » element method (Expand Search)
data modeling » data modelling (Expand Search), data models (Expand Search)
solved making » solved using (Expand Search)
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Algorithmic experimental parameter design.
Published 2024“…Furthermore, the estimation of the DOA can be accurately carried out under low signal-to-noise ratio conditions. This method effectively utilizes the degrees of freedom provided by the virtual array, reducing noise interference, and exhibiting better performance in terms of positioning accuracy and algorithm stability.…”
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Spatial spectrum estimation for three algorithms.
Published 2024“…Furthermore, the estimation of the DOA can be accurately carried out under low signal-to-noise ratio conditions. This method effectively utilizes the degrees of freedom provided by the virtual array, reducing noise interference, and exhibiting better performance in terms of positioning accuracy and algorithm stability.…”
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Scatter diagram of different principal elements.
Published 2025“…The experimental results show that the SSA-LightGBM model proposed in this paper has an average fault diagnosis accuracy of 93.6% after SSA algorithm optimization, which is 3.6% higher than before optimization. …”
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Algorithms runtime comparison.
Published 2025“…On this basis, considering the changes of customer demands and the speed of distribution network, a partheno-genetic hybrid simulated annealing algorithm is designed to solve the model by using the idea of disruption event processing combining immediate processing and scheduled batch processing. …”
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Solution results of different algorithms.
Published 2025“…On this basis, considering the changes of customer demands and the speed of distribution network, a partheno-genetic hybrid simulated annealing algorithm is designed to solve the model by using the idea of disruption event processing combining immediate processing and scheduled batch processing. …”
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Element model generation method with geometric distribution errors
Published 2025“…The product surface geometric distribution error is directly attached to the element nodes of the product ideal element model using the error surface reconstruction method and the replacement algorithm of the element node vector height based on the product’s point cloud data. …”
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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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Comparison of algorithm performance aesults.
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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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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