The Jiahao Shen Diaries

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The next posts are merged in Scholar. Their combined citations are counted just for the initial article.

This "Cited by" depend contains citations to the following content in Scholar. The ones marked * may be unique from your article while in 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 financial system is encountering quite possibly the most hard era of local climate modify further than precisely what is evident in the pre-industrial age. Despite the fact that Africa's share of global greenhouse gasoline (GHG) is minimal, the…

The next articles are merged in Scholar. Their merged citations are counted only for the primary article.

Towards attack-resistant route mutation for VANETs: an on the internet and adaptive multiagent reinforcement Discovering approach

A not-for-financial gain Business, IEEE is the earth's biggest complex professional Corporation committed to advancing technological innovation for the Jiahao Shen KCL advantage of humanity.

A QoE-pushed multicast approach with section routing—A novel multimedia targeted visitors engineering paradigm

The present era is struggling with a dilemma referring to participating the essentialities of Strength sources to attain financial prosperity as a consequence of the ensuing environmental complications. Consequently, sectors…

An optimized quantum minimum seeking algorithm with sure-success likelihood and its experiment simulation with Cirq

Monitoring environmental sustainability pathways in Africa: Do purely natural resource dependence, renewable Power, and technological innovations amplify or decrease the pollution noises?

Scanning radar forward-hunting superresolution imaging based on the Weibull distribution for the sea-surface target

This "Cited by" count consists of citations to the following article content in Scholar. The ones marked * may very well be different in the post 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。

The best way to disturb community reconnaissance: a relocating goal defense approach based on deep reinforcement learning

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