Missile thermal emission flow field under the synergistic effect of deep reinforcement learning and wireless sensor network

IF 2.1 4区计算机科学 Q3 COMPUTER SCIENCE, INFORMATION SYSTEMS

Wireless Networks Pub Date : 2023-09-07 DOI:10.1007/s11276-023-03415-4

Quanlin Zhou, Xinhong Xiong, Long Zhu, Guoxian Wang

引用次数: 0

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深度强化学习与无线传感器网络协同作用下的导弹热发射流场

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Wireless Networks 工程技术-电信学

CiteScore

7.70

自引率

3.30%

发文量

314

审稿时长

5.5 months

期刊介绍： The wireless communication revolution is bringing fundamental changes to data networking, telecommunication, and is making integrated networks a reality. By freeing the user from the cord, personal communications networks, wireless LAN''s, mobile radio networks and cellular systems, harbor the promise of fully distributed mobile computing and communications, any time, anywhere. Focusing on the networking and user aspects of the field, Wireless Networks provides a global forum for archival value contributions documenting these fast growing areas of interest. The journal publishes refereed articles dealing with research, experience and management issues of wireless networks. Its aim is to allow the reader to benefit from experience, problems and solutions described.