بدائل البحث:
mapping algorithm » making algorithm (توسيع البحث), mining algorithm (توسيع البحث), learning algorithm (توسيع البحث)
coding algorithm » cosine algorithm (توسيع البحث), modeling algorithm (توسيع البحث), finding algorithm (توسيع البحث)
element control » element controls (توسيع البحث), element content (توسيع البحث), dependent control (توسيع البحث)
element mapping » elemental mapping (توسيع البحث), element modeling (توسيع البحث), argument mapping (توسيع البحث)
mapping algorithm » making algorithm (توسيع البحث), mining algorithm (توسيع البحث), learning algorithm (توسيع البحث)
coding algorithm » cosine algorithm (توسيع البحث), modeling algorithm (توسيع البحث), finding algorithm (توسيع البحث)
element control » element controls (توسيع البحث), element content (توسيع البحث), dependent control (توسيع البحث)
element mapping » elemental mapping (توسيع البحث), element modeling (توسيع البحث), argument mapping (توسيع البحث)
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Division map of the delivery area.
منشور في 2025"…First, the paper systematically sorts out the classification and definition of no-fly zones as well as their impact mechanisms on UAV path planning, and elaborates on the theoretical basis of vehicle-UAV collaborative delivery, including the constituent elements of the problem, methods for quantifying customer satisfaction, and the application framework of heuristic algorithms. …"
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Convergence curve of the DBO algorithm.
منشور في 2025"…The improved Dung Beetle Optimization algorithm, Back Propagation Neural Network, Finite Element Analysis, and Response Surface Methodology provide a strong guarantee for the selection of robot polishing process parameters. …"
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Codes for "<b>A coherent power-load optimization algorithm for wind-farm-level yaw control considering wake effects via deep neural network</b>"
منشور في 2024"…<p dir="ltr">Codes for "<b>A coherent power-load optimization algorithm for wind-farm-level yaw control considering wake effects via deep neural network</b>"</p>…"
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Comparison of mAP curves in ablation experiments.
منشور في 2025"…Experimental results on a self-constructed dataset demonstrate the improved model efficacy, achieving 92.0% precision, 80.8% recall, 87.0% mean Average Precision (mAP@0.5), and 81.79 FPS detection speed. Compared to the original YOLOv8 model, the improved algorithm shows increases of 2.2% in precision, 0.6% in recall, and 2.0% in mAP@0.5, with a detection speed improvement of 65.48 FPS. …"
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