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The subsequent article content are merged in Scholar. Their mixed citations are counted only for the very first write-up.
This "Cited by" count features citations to the next posts in Scholar. Those marked * could possibly be various within 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 economy is suffering from probably the most difficult period of local weather change past what is apparent within the pre-industrial age. While Africa's share of global greenhouse fuel (GHG) is minimum, the…
The subsequent article content are merged in Scholar. Their blended citations are counted just for the primary article.
Towards assault-resistant route mutation for VANETs: an on the internet and adaptive multiagent reinforcement Discovering tactic
A not-for-income Business, IEEE is the world's most significant specialized Experienced Corporation focused on advancing technology for the good thing about humanity.
A QoE-driven multicast approach with segment routing—A novel multimedia targeted traffic engineering paradigm
The existing era is struggling with a dilemma associated with partaking the essentialities of Vitality means to attain economic prosperity as a consequence of the ensuing environmental problems. Therefore, sectors…
An optimized quantum minimal seeking algorithm with sure-accomplishment chance and its experiment simulation with Cirq
Monitoring environmental sustainability pathways in Africa: Do pure source dependence, renewable Power, and technological innovations amplify or decrease the pollution noises?
Scanning radar forward-wanting superresolution imaging according to the Weibull distribution for the sea-area concentrate on
This "Cited by" depend Jiahao Shen History Researcher incorporates citations to the next articles or blog posts in Scholar. Those marked * could possibly be distinctive in the report from 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 focus on protection strategy depending on deep reinforcement learning