بدائل البحث:
method algorithm » network algorithm (توسيع البحث), means algorithm (توسيع البحث), mean algorithm (توسيع البحث)
complement rast » complement past (توسيع البحث), complement 5a (توسيع البحث), complement rim4 (توسيع البحث)
rast algorithm » best algorithm (توسيع البحث), forest algorithm (توسيع البحث), based algorithm (توسيع البحث)
level finding » novel findings (توسيع البحث), review finding (توسيع البحث), level coding (توسيع البحث)
element » elements (توسيع البحث)
method algorithm » network algorithm (توسيع البحث), means algorithm (توسيع البحث), mean algorithm (توسيع البحث)
complement rast » complement past (توسيع البحث), complement 5a (توسيع البحث), complement rim4 (توسيع البحث)
rast algorithm » best algorithm (توسيع البحث), forest algorithm (توسيع البحث), based algorithm (توسيع البحث)
level finding » novel findings (توسيع البحث), review finding (توسيع البحث), level coding (توسيع البحث)
element » elements (توسيع البحث)
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Overview of the C&CG method.
منشور في 2025"…The model is solved iteratively using the column generation algorithm and strong duality theory. Case studies on a Northeast China power grid demonstrate that, by optimally configuring generation and storage capacity guided by flexibility and other indicators, the proposed method reduces curtailment/load shedding costs and system flexibility insufficiency probability by 45% and 4.3% respectively. …"
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Spatial spectrum estimation for three algorithms.
منشور في 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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Multi-material topology optimization using scaled boundary finite element method
منشور في 2025"…<p>This work introduces the use of Scaled Boundary Finite Element Method (SBFEM) in Multi-Material Topology Optimization (MMTO) problems, which is new in the literature. …"
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Data Sheet 1_Clinical validation of an artificial intelligence algorithm for classifying tuberculosis and pulmonary findings in chest radiographs.pdf
منشور في 2025"…</p>Results<p>In the internal validation, the Lung Abnormality and Tuberculosis models achieved an AUC of 0.94, while the Radiological Findings model yielded a mean AUC of 0.84. During the external validation, utilizing the ground truth generated by board-certified thoracic radiologists, the algorithm achieved better sensitivity in 6 out of 11 classes than physicians with varying experience levels. …"
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