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The following articles are merged in Scholar. Their merged citations are counted just for the very first posting.
This "Cited by" depend contains citations to the following content in Scholar. Those marked * may very well be unique 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 economic system is encountering the most challenging period of climate adjust beyond precisely what is evident while in the pre-industrial age. Even though Africa's share of world greenhouse gas (GHG) is small, the…
The following article content are merged in Scholar. Their blended citations are counted only for the primary article.
Towards assault-resistant route mutation for VANETs: Jiahao Shen King's College London an on the internet and adaptive multiagent reinforcement learning technique
A not-for-profit Group, IEEE is the world's premier specialized Qualified organization committed to advancing technologies for the advantage of humanity.
A QoE-pushed multicast method with phase routing—A novel multimedia visitors engineering paradigm
The existing era is going through a Predicament referring to partaking the essentialities of energy assets to achieve economic prosperity as a result of the following environmental troubles. As a result, sectors…
An optimized quantum minimum seeking algorithm with guaranteed-achievement likelihood and its experiment simulation with Cirq
Monitoring environmental sustainability pathways in Africa: Do natural source dependence, renewable Electricity, and technological innovations amplify or reduce 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 features citations to the following articles or blog posts in Scholar. Those marked * may be various through the posting inside 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。
Tips on how to disturb community reconnaissance: a shifting focus on protection solution dependant on deep reinforcement learning