Suchergebnisse - "A3C algorithm"

Blockchain-Based Edge Computing Resource Allocation in IoT: A Deep Reinforcement Learning Approach von He, Ying, Wang, Yuhang, Qiu, Chao, Lin, Qiuzhen, Li, Jianqiang, Ming, Zhong

“… With the exponential growth in the number of Internet-of-Things (IoT) devices, the cloud-centric computing paradigm can hardly meet the increasingly high …”
Volltext

A3C-Based Intelligent Event-Triggering Control of Networked Nonlinear Unmanned Marine Vehicles Subject to Hybrid Attacks von Ye, Zehua, Zhang, Dan, Wu, Zheng-Guang, Yan, Huaicheng

“… This paper is concerned with the intelligent event-triggering-based positioning control of networked unmanned marine vehicle (UMV) systems with hybrid attacks, …”
Volltext

Workflow scheduling based on asynchronous advantage actor–critic algorithm in multi-cloud environment von Tang, Xuhao, Liu, Fagui, Wang, Bin, Xu, Dishi, Jiang, Jun, Wu, Qingbo, Chen, C.L. Philip

“… Recently, the multi-cloud environment (MCE) has increasingly become the preferred choice of users. As with the cloud environment, efficient workflow scheduling …”
Volltext

A multi-objective decision-making method for small modular reactor operation based on A3C algorithm von Cheng, Shouyu, Gu, Chengyan, Zhang, Bowen, Wang, Shibo, Yan, Chengxing

“… Small modular reactors (SMRs) are ideal energy sources for remote areas, but they still require operators to make decisions. Due to the harsh working …”
Volltext

Multi-market agency-based power procurement strategies for power grid companies using reinforcement learning von Wang, Boyu, Xu, Xiaofeng, Wang, Peng

“… At this critical stage of simultaneously advancing the construction of a new power system and power market reform, power grid companies face challenges in …”
Volltext

Analysis of effective integration of information platform courses and daily teaching in universities based on adaptive network von Ma, Jing

“… This paper first analyzes the effective application of web platforms and information technology in college teaching and constructs a web-based teaching aid …”
Volltext

Adaptive Sharding for UAV Networks: A Deep Reinforcement Learning Approach to Blockchain Optimization von Lu, Kaiyin, Zhang, Xinguang, Zhai, Tianbo, Zhou, Mengjie

“… As unmanned aerial vehicle (UAV) technology expands into diverse applications, the demand for enhanced performance intensifies. Blockchain sharding technology …”
Volltext

Spatial arrangement using deep reinforcement learning to minimise rearrangement in ship block stockyards von Kim, Byeongseop, Jeong, Yongkuk, Shin, Jong Gye

“… As the shipbuilding industry is an engineering-to-order industry, different types of products are manufactured according to customer requests, and each product …”
Volltext

On-Chain and Off-Chain Data Management for Blockchain-Internet of Things: A Multi-Agent Deep Reinforcement Learning Approach von Tsang, Y. P., Lee, C. K. M., Zhang, Kening, Wu, C. H., Ip, W. H.

“… The emergence of blockchain technology has seen applications increasingly hybridise cloud storage and distributed ledger technology in the Internet of Things …”
Volltext

A3C-Based Interference Cancellation Algorithm for Cognitive Internet of Things Communication von LIU Xinmeng, XIE Jianli, LI Cuiran, WANG Yiming

“… To address the intelligent needs of spectrum resource interference management, in this study, an Asynchronous Advantage Actor-Critic(A3C)-based intelligent …”
Volltext

A study of electricity sales offer strategies applicable to the participation of multi-energy generators in short- and medium-term markets von Wang, Boyu, Xu, Xiaofeng, Li, Genzhu, Fan, Hang, Qiao, Ning, Chen, Haidong, Liu, Dunnan, Ma, Tongtao

“… Due to the increasing proportion of renewable energy, a multi-layered and multi-timescale energy market has emerged in many countries such as China. In the …”
Volltext

A Parallel Framework for Fast Charge/Discharge Scheduling of Battery Storage Systems in Microgrids von Huang, Wei-Tzer, Chung, Wu-Chun, Wu, Chao-Chin, Huang, Tse-Yun

“… Fast charge/discharge scheduling of battery storage systems is essential in microgrids to effectively balance variable renewable energy sources, meet …”
Volltext

Time-Varying Weights in Multi-Reward Architecture for Deep Reinforcement Learning von Xu, Meng, Chen, Xinhong, She, Yechao, Jin, Yang, Wang, Jianping

“… Deep Reinforcement Learning (DRL) has recently been focused on extracting more knowledge from the reward signal to improve sample efficiency. The Multi-Reward …”
Volltext

Cooperative traffic signal control using Multi-step return and Off-policy Asynchronous Advantage Actor-Critic Graph algorithm von Yang, Shantian, Yang, Bo, Wong, Hau-San, Kang, Zhongfeng

“… Intelligent traffic signal control helps to reduce traffic congestion and thus has been studied for a few decades. Multi-intersection cooperative traffic …”
Volltext

Research on Offloading and Resource Allocation for MEC with Energy Harvesting Based on Deep Reinforcement Learning von Chen, Jun, Mi, Junyu, Guo, Chen, Fu, Qing, Tang, Weidong, Luo, Wenlang, Zhu, Qing

“… Mobile edge computing (MEC) systems empowered by energy harvesting (EH) significantly enhance sustainable computing capabilities for mobile devices (MDs). This …”
Volltext

Deep Reinforcement Learning for Real-Time Airport Emergency Evacuation Using Asynchronous Advantage Actor–Critic (A3C) Algorithm von Zhou, Yujing, Yang, Yupeng, Pan, Bill Deng, Liu, Yongxin, Namilae, Sirish, Song, Houbing Herbert, Liu, Dahai

“… Emergencies can occur unexpectedly and require immediate action, especially in aviation, where time pressure and uncertainty are high. This study focused on …”
Volltext

Research on Cooperation Between Wind Farm and Electric Vehicle Aggregator Based on A3C Algorithm von Pan, Yang, Wang, Weiye, Li, Yanbin, Zhang, Feng, Sun, Yanting, Liu, Dunnan

“… As renewable energy sources such as wind are connected to the grid on a large scale, the safe and stable operation of the power system is facing challenges and …”
Volltext

Introducing Event-Based Communication in Asynchronous Advantage Actor-Critic Algorithm von Sunai, Hiroki, Kobayashi, Koichi, Yamashita, Yuh

“… Distributed reinforcement learning is a method for learning by multiple agents in parallel. In distributed reinforcement learning, one of the challenge topics …”
Volltext

A3C-Based Model-Free Adaptive Fault-Tolerant Control for Intelligent Ships with an Extended State Observer von Xu, Chengqi, Liu, Jialun, Li, Shijie, Dong, Zhilin, Hu, Xinjue

“… A new fault-tolerant control (FTC) method based on the advantage actor-critic (A3C) learning model-free adaptive control (MFAC) is proposed for intelligent …”
Volltext

Intelligent Task Scheduling for Microservices via A3C-Based Reinforcement Learning von Wang, Yang, Tang, Tengda, Fang, Zhou, Deng, Yingnan, Duan, Yifei

“… To address the challenges of high resource dynamism and intensive task concurrency in microservice systems, this paper proposes an adaptive resource scheduling …”
Volltext