- 期刊
A Reinforcement Learning Agent for Dynamic Power Management in Embedded Systems
並列摘要
The use of effective power management strategies is essential in improving the power utilization efficiency and battery endurance of embedded systems. Accordingly, this paper presents a dynamic power management mechanism based on a reinforcement learning agent to adaptively manage the power consumption and service achievability of an embedded system device. The simulation results show that for a given set of environmental conditions, the proposed mechanism yields a notable improvement in both the power utilization efficiency and the battery endurance of the embedded system compared to that obtained using a static power management scheme.
被引用紀錄
楊任軒（2009）。離岸風場併入輸電系統之研究〔碩士論文，國立臺北科技大學〕。華藝線上圖書館。https://www.airitilibrary.com/Article/Detail?DocID=U0006-2007200909473000
莊東華（2009）。離岸風場併入不同併接點之系統衝擊研究〔碩士論文，國立臺北科技大學〕。華藝線上圖書館。https://www.airitilibrary.com/Article/Detail?DocID=U0006-2207200922415500
延伸閱讀
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