STRI
发表于 2025-3-21 18:20:11
书目名称Mineral Dust影响因子(影响力)<br> http://figure.impactfactor.cn/if/?ISSN=BK0634427<br><br> <br><br>书目名称Mineral Dust影响因子(影响力)学科排名<br> http://figure.impactfactor.cn/ifr/?ISSN=BK0634427<br><br> <br><br>书目名称Mineral Dust网络公开度<br> http://figure.impactfactor.cn/at/?ISSN=BK0634427<br><br> <br><br>书目名称Mineral Dust网络公开度学科排名<br> http://figure.impactfactor.cn/atr/?ISSN=BK0634427<br><br> <br><br>书目名称Mineral Dust被引频次<br> http://figure.impactfactor.cn/tc/?ISSN=BK0634427<br><br> <br><br>书目名称Mineral Dust被引频次学科排名<br> http://figure.impactfactor.cn/tcr/?ISSN=BK0634427<br><br> <br><br>书目名称Mineral Dust年度引用<br> http://figure.impactfactor.cn/ii/?ISSN=BK0634427<br><br> <br><br>书目名称Mineral Dust年度引用学科排名<br> http://figure.impactfactor.cn/iir/?ISSN=BK0634427<br><br> <br><br>书目名称Mineral Dust读者反馈<br> http://figure.impactfactor.cn/5y/?ISSN=BK0634427<br><br> <br><br>书目名称Mineral Dust读者反馈学科排名<br> http://figure.impactfactor.cn/5yr/?ISSN=BK0634427<br><br> <br><br>
大都市
发表于 2025-3-21 21:09:07
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DOLT
发表于 2025-3-22 01:32:15
978-94-024-0651-1Springer Science+Business Media Dordrecht 2014
跳动
发表于 2025-3-22 07:03:20
Peter Knippertz,Jan-Berend W. StuutCovers the whole breadth of mineral dust research, from a scientific perspective.Presents interdisciplinary work including results from field campaigns, satellite observations, laboratory studies, com
Prognosis
发表于 2025-3-22 09:06:01
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取消
发表于 2025-3-22 16:28:19
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欢呼
发表于 2025-3-22 20:53:21
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反话
发表于 2025-3-22 21:33:49
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negligence
发表于 2025-3-23 02:28:58
,PET Annotation Visualizer: A Tool to Visualize the Process Model Extraction from Text (PET) Datasetons and can be easily integrated into existing workflows or extend the function implemented. During the system presentation, we demonstrate the effectiveness of the tool and its potential impact in improving process extraction from text tasks. The tool is freely available as a Python package at ..
啮齿动物
发表于 2025-3-23 07:07:19
Non-Local Approach to Weak Interactions, genetic algorithm (GA), ant colony optimization (ACO), particle swarm optimization (PSO) and chaotic binary particle swarm optimization (CBPSO). Experiments demonstrate that the proposed algorithm could achieve the minimal reduct more efficiently than the other methods.