Search alternatives:
well optimization » wolf optimization (Expand Search), whale optimization (Expand Search), field optimization (Expand Search)
based objective » based object (Expand Search), based selective (Expand Search), based objects (Expand Search)
binary based » library based (Expand Search), linac based (Expand Search), binary mask (Expand Search)
based well » based cell (Expand Search), based web (Expand Search), based all (Expand Search)
lens » less (Expand Search)
well optimization » wolf optimization (Expand Search), whale optimization (Expand Search), field optimization (Expand Search)
based objective » based object (Expand Search), based selective (Expand Search), based objects (Expand Search)
binary based » library based (Expand Search), linac based (Expand Search), binary mask (Expand Search)
based well » based cell (Expand Search), based web (Expand Search), based all (Expand Search)
lens » less (Expand Search)
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Proposed Algorithm.
Published 2025“…The objective is to optimize binary offloading decisions under dynamic wireless channel conditions and energy harvesting constraints. …”
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Comparisons between ADAM and NADAM optimizers.
Published 2025“…The objective is to optimize binary offloading decisions under dynamic wireless channel conditions and energy harvesting constraints. …”
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SHAP bar plot.
Published 2025“…<div><p>Background</p><p>The high prevalence of cognitive impairment (CI) in Chronic kidney disease (CKD) patients impacts their quality of life and prognosis, yet risk prediction models for CI in this population remain underexplored.</p><p>Objective</p><p>This study aimed to develop a risk prediction model for CI in CKD patients using machine learning algorithms, with the objective of enhancing risk prediction accuracy and facilitating early intervention.…”
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Sample screening flowchart.
Published 2025“…<div><p>Background</p><p>The high prevalence of cognitive impairment (CI) in Chronic kidney disease (CKD) patients impacts their quality of life and prognosis, yet risk prediction models for CI in this population remain underexplored.</p><p>Objective</p><p>This study aimed to develop a risk prediction model for CI in CKD patients using machine learning algorithms, with the objective of enhancing risk prediction accuracy and facilitating early intervention.…”
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Descriptive statistics for variables.
Published 2025“…<div><p>Background</p><p>The high prevalence of cognitive impairment (CI) in Chronic kidney disease (CKD) patients impacts their quality of life and prognosis, yet risk prediction models for CI in this population remain underexplored.</p><p>Objective</p><p>This study aimed to develop a risk prediction model for CI in CKD patients using machine learning algorithms, with the objective of enhancing risk prediction accuracy and facilitating early intervention.…”
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SHAP summary plot.
Published 2025“…<div><p>Background</p><p>The high prevalence of cognitive impairment (CI) in Chronic kidney disease (CKD) patients impacts their quality of life and prognosis, yet risk prediction models for CI in this population remain underexplored.</p><p>Objective</p><p>This study aimed to develop a risk prediction model for CI in CKD patients using machine learning algorithms, with the objective of enhancing risk prediction accuracy and facilitating early intervention.…”
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ROC curves for the test set of four models.
Published 2025“…<div><p>Background</p><p>The high prevalence of cognitive impairment (CI) in Chronic kidney disease (CKD) patients impacts their quality of life and prognosis, yet risk prediction models for CI in this population remain underexplored.</p><p>Objective</p><p>This study aimed to develop a risk prediction model for CI in CKD patients using machine learning algorithms, with the objective of enhancing risk prediction accuracy and facilitating early intervention.…”
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Display of the web prediction interface.
Published 2025“…<div><p>Background</p><p>The high prevalence of cognitive impairment (CI) in Chronic kidney disease (CKD) patients impacts their quality of life and prognosis, yet risk prediction models for CI in this population remain underexplored.</p><p>Objective</p><p>This study aimed to develop a risk prediction model for CI in CKD patients using machine learning algorithms, with the objective of enhancing risk prediction accuracy and facilitating early intervention.…”
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An Example of a WPT-MEC Network.
Published 2025“…The objective is to optimize binary offloading decisions under dynamic wireless channel conditions and energy harvesting constraints. …”
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Related Work Summary.
Published 2025“…The objective is to optimize binary offloading decisions under dynamic wireless channel conditions and energy harvesting constraints. …”
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Simulation parameters.
Published 2025“…The objective is to optimize binary offloading decisions under dynamic wireless channel conditions and energy harvesting constraints. …”
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Training losses for N = 10.
Published 2025“…The objective is to optimize binary offloading decisions under dynamic wireless channel conditions and energy harvesting constraints. …”
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Normalized computation rate for N = 10.
Published 2025“…The objective is to optimize binary offloading decisions under dynamic wireless channel conditions and energy harvesting constraints. …”
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Summary of Notations Used in this paper.
Published 2025“…The objective is to optimize binary offloading decisions under dynamic wireless channel conditions and energy harvesting constraints. …”
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A new fast filtering algorithm for a 3D point cloud based on RGB-D information
Published 2019“…This method aligns the color image to the depth image, and the color mapping image is converted to an HSV image. Then, the optimal segmentation threshold of the V image that is calculated by using the Otsu algorithm is applied to segment the color mapping image into a binary image, which is used to extract the valid point cloud from the original point cloud with outliers. …”
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Data Sheet 1_Detection of litchi fruit maturity states based on unmanned aerial vehicle remote sensing and improved YOLOv8 model.docx
Published 2025“…In addition, YOLOv8-FPDW was more competitive than mainstream object detection algorithms. The study predicted the optimal harvest period for litchis, providing scientific support for orchard batch harvesting and fine management.…”
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Analysis and design of algorithms for the manufacturing process of integrated circuits
Published 2023“…The (approximate) solution proposals of state-of-the-art methods include rule-based approaches, genetic algorithms, and reinforcement learning. …”