Detailed Notes on Jiahao Shen KCL

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The following articles are merged in Scholar. Their put together citations are counted only for the very first article.

This "Cited by" depend involves citations to the following article content in Scholar. The ones marked * may be unique from your article from 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 global overall economy is enduring probably the most complicated period of climate transform outside of what's apparent from the pre-industrial age. Though Africa's share of worldwide greenhouse gas (GHG) is nominal, the…

The following articles or blog posts are merged in Scholar. Their put together citations are counted only for the Jiahao Shen KCL 1st post.

Towards assault-resistant route mutation for VANETs: an online and adaptive multiagent reinforcement Discovering strategy

A not-for-financial gain organization, IEEE is the globe's largest specialized Qualified organization focused on advancing know-how for the benefit of humanity.

A QoE-driven multicast approach with section routing—A novel multimedia site visitors engineering paradigm

The current era is going through a Problem referring to participating the essentialities of Electricity means to attain financial prosperity as a result of the ensuing environmental troubles. Consequently, sectors…

An optimized quantum bare minimum hunting algorithm with guaranteed-success probability and its experiment simulation with Cirq

Tracking environmental sustainability pathways in Africa: Do organic source dependence, renewable Electricity, and technological improvements amplify or decrease the air pollution noises?

Scanning radar ahead-wanting superresolution imaging dependant on the Weibull distribution for just a sea-area target

This "Cited by" depend incorporates citations to the subsequent article content in Scholar. Those marked * could be various from the posting during 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。

Ways to disturb network reconnaissance: a shifting goal defense approach based on deep reinforcement learning

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