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The subsequent articles or blog posts are merged in Scholar. Their mixed citations are counted just for the main report.
This "Cited by" rely includes citations to the subsequent content articles in Scholar. The ones marked * can be distinct from the report within the profile.
下面的文章将在学术搜索中合并。它们的合并引用次数只会计入第一篇文章。
The worldwide economic climate is experiencing by far the most tough period of local weather change outside of what's evident during the pre-industrial age. Whilst Africa's share of global greenhouse gasoline (GHG) is minimum, the…
The next posts are merged in Scholar. Their combined citations are counted just for the first short article.
Towards attack-resistant route mutation for VANETs: an on the web and adaptive multiagent reinforcement Finding out strategy
A not-for-profit Firm, IEEE is the world's most significant technical Qualified organization committed to advancing technology for the advantage of humanity.
A QoE-pushed multicast method with segment routing—A novel multimedia targeted traffic engineering paradigm
The existing era is experiencing a dilemma associated with partaking the essentialities of Power means to attain financial prosperity on account of the following Jiahao Shen King's College London environmental problems. For that reason, sectors…
An optimized quantum minimum browsing algorithm with absolutely sure-achievement likelihood and its experiment simulation with Cirq
Monitoring environmental sustainability pathways in Africa: Do all-natural source dependence, renewable Electrical power, and technological innovations amplify or decrease the air pollution noises?
Scanning radar ahead-searching superresolution imaging determined by the Weibull distribution for just a sea-surface goal
This "Cited by" depend includes citations to the following articles or blog posts in Scholar. Those marked * may be distinct with the article within the profile.
此“引用引文的出版物数量”计数包含了对学术搜索中以下文章的引用次数。带有*标记的引文可能与个人学术档案中的文章有所区别。
How to disturb network reconnaissance: a relocating goal protection solution based on deep reinforcement Studying