بدائل البحث:
next algorithm » new algorithm (توسيع البحث), best algorithm (توسيع البحث), pelt algorithm (توسيع البحث)
data algorithm » data algorithms (توسيع البحث), update algorithm (توسيع البحث), atlas algorithm (توسيع البحث)
data finding » path finding (توسيع البحث), data fitting (توسيع البحث), case finding (توسيع البحث)
develop next » develop new (توسيع البحث), develop entv (توسيع البحث), develop post (توسيع البحث)
element data » settlement data (توسيع البحث), relevant data (توسيع البحث), movement data (توسيع البحث)
next algorithm » new algorithm (توسيع البحث), best algorithm (توسيع البحث), pelt algorithm (توسيع البحث)
data algorithm » data algorithms (توسيع البحث), update algorithm (توسيع البحث), atlas algorithm (توسيع البحث)
data finding » path finding (توسيع البحث), data fitting (توسيع البحث), case finding (توسيع البحث)
develop next » develop new (توسيع البحث), develop entv (توسيع البحث), develop post (توسيع البحث)
element data » settlement data (توسيع البحث), relevant data (توسيع البحث), movement data (توسيع البحث)
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The run time for each algorithm in seconds.
منشور في 2025"…We find evidence that the generalised GLS-KGR algorithm is well-suited to such time-series applications, outperforming several standard techniques on this dataset.…"
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The structure of FasterNext.
منشور في 2025"…<div><p>The rapid development of Internet of Things (IoT) technology and deep learning has propelled the deployment of vision-based fire detection algorithms on edge devices, significantly exacerbating the trade-off between accuracy and inference speed under hardware resource constraints. …"
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Data Sheet 1_A method for finding epistatic effects of maternal and fetal variants.docx
منشور في 2025"…Though the epistasis-mining algorithms MDR-PDT, TrioFS, and EPISFA-LD were originally designed to find epistatic offspring variants, we generalize them to include maternal SNPs and search more broadly. …"
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Parameters of the FasterNext and C3.
منشور في 2025"…<div><p>The rapid development of Internet of Things (IoT) technology and deep learning has propelled the deployment of vision-based fire detection algorithms on edge devices, significantly exacerbating the trade-off between accuracy and inference speed under hardware resource constraints. …"
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