优化 WSN 中的能源资源：ARIMA 特征选择与自适应强化学习的结合

IF 2.3 4区物理与天体物理 Q2 OPTICS

Fiber and Integrated Optics Pub Date : 2024-05-31 DOI:10.1080/01468030.2024.2342269

S Anslam Sibi, L Sherly Puspha Annabel

引用次数: 0

摘要

WSN 中高效的能量管理对于延长网络寿命和保持性能至关重要。本研究介绍了一种新颖的能量优化方法，通过整合...

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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Optimizing Energy Resources in WSNs: ARIMA Feature Selection Meets Adaptive Reinforcement Learning

Efficient energy management in WSNs is pivotal for prolonged network lifetime and sustained performance. This research introduces a novel approach to energy optimization through the integration of ...

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来源期刊

Fiber and Integrated Optics 物理-光学

CiteScore

3.40

自引率

0.00%

发文量

审稿时长

>12 weeks

期刊介绍： Fiber and Integrated Optics , now incorporating the International Journal of Optoelectronics, is an international bimonthly journal that disseminates significant developments and in-depth surveys in the fields of fiber and integrated optics. The journal is unique in bridging the major disciplines relevant to optical fibers and electro-optical devices. This results in a balanced presentation of basic research, systems applications, and economics. For more than a decade, Fiber and Integrated Optics has been a valuable forum for scientists, engineers, manufacturers, and the business community to exchange and discuss techno-economic advances in the field.