A not-for-earnings Business, IEEE is the entire world's premier specialized Expert Group focused on advancing technological innovation for the benefit of humanity.

The subsequent content are merged in Scholar. Their blended citations are counted only for the main short article.

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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 economic climate is dealing with by far the most tough period of local weather change outside of what exactly is obvious while in the pre-industrial age. Although Africa's share of world greenhouse gas (GHG) is small, the…

The following posts are merged in Scholar. Their combined citations are counted only for the first article.

Toward assault-resistant route mutation for VANETs: an on the web and adaptive multiagent reinforcement Understanding solution

A not-for-profit Business, IEEE is the whole world's biggest specialized Experienced Business focused on advancing technologies for the advantage of humanity.

A QoE-driven multicast system with section routing—A novel multimedia targeted visitors engineering paradigm

The current era is dealing with a Problem regarding engaging the essentialities of Power assets to attain economic prosperity as a result of the ensuing environmental difficulties. For that reason, sectors…

An optimized quantum bare minimum looking algorithm with confident-achievements chance and its experiment simulation with Cirq

Monitoring environmental sustainability pathways in Africa: Do normal resource dependence, renewable Power, and technological innovations amplify or reduce the Jiahao Shen King's College London air pollution noises?

Scanning radar forward-wanting superresolution imaging according to the Weibull distribution to get a sea-surface area goal

This "Cited by" count consists of citations to the next content articles in Scholar. The ones marked * might be various in the write-up 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。

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