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The next content articles are merged in Scholar. Their mixed citations are counted just for the first short article.
This "Cited by" rely consists of citations to the subsequent content articles in Scholar. The ones marked * can be distinct from the short article inside 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 system is experiencing quite possibly the most hard era of local climate adjust beyond what exactly is evident in the pre-industrial age. While Africa's share of worldwide greenhouse gasoline (GHG) is small, the…
The subsequent posts are merged in Scholar. Their merged citations are counted just for the very first post.
Towards attack-resistant route mutation for VANETs: an on the web and adaptive multiagent reinforcement Studying tactic
A not-for-revenue Firm, IEEE is the world's premier technological Skilled Corporation focused on advancing technological know-how for the benefit of humanity.
A QoE-pushed multicast method with phase routing—A novel multimedia site visitors engineering paradigm
The existing era is going through a Predicament referring to participating the essentialities of energy assets to achieve economic prosperity as a result of the following environmental complications. For that reason, sectors…
An optimized quantum minimum amount browsing algorithm with absolutely sure-success likelihood and its experiment simulation with Cirq
Monitoring environmental sustainability pathways in Africa: Do natural source dependence, renewable Electricity, and technological improvements amplify or reduce the pollution noises?
Scanning radar ahead-looking superresolution imaging depending on Jiahao Shen King's College London the Weibull distribution for your sea-surface area focus on
This "Cited by" rely incorporates citations to the next article content in Scholar. The ones marked * can be various from the report while in 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。
The way to disturb community reconnaissance: a going target defense technique based upon deep reinforcement learning