Search Results - "deep reinforcement learning algorithm"

A deep reinforcement learning approach to energy management control with connected information for hybrid electric vehicles by Mei, Peng, Karimi, Hamid Reza, Xie, Hehui, Chen, Fei, Huang, Cong, Yang, Shichun

“…Considering the importance of the energy management strategy for hybrid electric vehicles, this paper is aiming at addressing the energy optimization control…”
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Multi-robot path planning based on a deep reinforcement learning DQN algorithm by Yang, Yang, Juntao, Li, Lingling, Peng

“…The unmanned warehouse dispatching system of the ‘goods to people’ model uses a structure mainly based on a handling robot, which saves considerable manpower…”
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An applied deep reinforcement learning approach to control active networked microgrids in smart cities with multi-level participation of battery energy storage system and electric vehicles by Sepehrzad, Reza, Langeroudi, Amir Saman Godazi, Khodadadi, Amin, Adinehpour, Sara, Al-Durra, Ahmed, Anvari-Moghaddam, Amjad

“…•Multi-layers NMG energy management based on the RES and EVs uncertainties.•Improving NMG transient stability based on deep reinforcement learning…”
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Digital Twin-Assisted Federated Learning Service Provisioning Over Mobile Edge Networks by Zhang, Ruirui, Xie, Zhenzhen, Yu, Dongxiao, Liang, Weifa, Cheng, Xiuzhen

“…Federated Learning (FL) offers collaborative machine learning without data exposure, but challenges arise in the mobile edge network (MEC) environment due to…”
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Energy management system scheduling optimization based on an improved generative adversarial network deep reinforcement learning algorithm by Chao, Weipeng, Shi, Yuanbo, Li, Yushuai, Liu, Meng, Leng, Xiaoling

“…Households, as electricity consumers, play a critical role in achieving the carbon peak and carbon neutrality goals. The development of smart grids provides…”
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Intelligently Joint Task Assignment and Trajectory Planning for UAV Cluster With Limited Communication by Lu, Zhuo, Wu, Guangyu, Zhou, Fuhui, Wu, Qihui

“…The intelligent collaborative execution of tasks by unmanned aerial vehicle (UAV) clusters has received an increasing attention. However, the quality of…”
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A hybrid MARL clustering framework for real time open pit mine truck scheduling by Xiang, Xiaolei, Lin, Wei, Li, Danqi

“…This paper proposes an innovative approach that combines a QMIX algorithm (a multi-agent deep reinforcement learning algorithm, MADRL) with a Gaussian Mixture…”
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FlexSim-Simulated PCB Assembly Line Optimization Using Deep Q-Network by Jinhao Du, Jabir Mumtaz, Wenxi Zhao, Jian Huang

“…The balance scheduling of Printed Circuit Board (PCB) assembly lines plays a crucial role in enhancing production efficiency. Traditional scheduling methods…”
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Data driven frequency control of isolated microgrids based on priority experience replay soft deep reinforcement learning algorithm by Wu, Zifan, Lv, Zheng, Huang, Xiongwei, Li, Zhen

“…This paper addresses the trade-off between frequency control performance and cost in islanded microgrids, where higher performance requires higher cost. We…”
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Adaptive regulation of blood glucose levels: A triadic methodology incorporating super twisting and deep policy gradient by Mohammadzadeh, Ardashir, Alattas, Khalid A.

“…•Developing a Super-Twisting Sliding Mode Control (SSMC) for blood glucose regulation.•Integrating a Deep Reinforcement Learning (DRL) algorithm to optimize…”
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A High Reliable Computing Offloading Strategy Using Deep Reinforcement Learning for IoVs in Edge Computing by Wang, Kun, Wang, Xiaofeng, Liu, Xuan

“…In view of the serious problems of increasing delay energy consumption and decreasing service quality caused by complex network state and massive computing…”
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Deep Reinforcement Learning for Mobility-Aware Digital Twin Migrations in Edge Computing by Zhang, Yuncan, Wang, Luying, Liang, Weifa

“…The past decade witnessed an explosive growth on the number of IoT devices (objects/suppliers), including portable mobile devices, autonomous vehicles, sensors…”
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Energy Management in Electric Vehicles Using Improved Swarm Optimized Deep Reinforcement Learning Algorithm by Jawale, M. A., Pawar, A. B., Korde, Sachin K., Rakshe, Dhananjay S., William, P., Deshpande, Neeta

“…The internal combustion engine-based transportation system is causing severe problems such as rising levels of pollution, rising petroleum prices, and the…”
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ADAS-RL: Safety learning approach for stable autonomous driving by Lee, Dongsu, Kwon, Minhae

“…Stability is the most significant component of an autonomous driving system, affecting both the lives of drivers and pedestrians and traffic flow…”
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Research on international logistics supply chain management strategy based on deep reinforcement learning by Wang, Yuzhen, Wang, Jian

“…The use of deep reinforcement learning algorithms for strategy formulation in supply chain management enables the nodes in the supply chain to better improve…”
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Optimization of DC Microgrid Power and Energy Management in the Presence of Small-Scale Wind Turbine Integration and Renewable Load Shedding by Zhang, Hao

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Optimisation of remanufacturing supply chain with dual recycling channels under improved deep reinforcement learning algorithm by Wang, Zhen, Ye, Chunming, Guo, Jianquan

“…To address the challenge of reducing carbon emissions in the automotive industry, new energy vehicles (NEVs) have emerged, leading to an increase in the number…”
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Research on the implementation and effectiveness evaluation of deep reinforcement learning algorithms for portfolio optimisation by Yunxiang, Gao, Bangying, Tang

“…Portfolio optimisation is the process of continuously allocating money to different assets to maximize returns, and since the theory was introduced in 1952,…”
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Low-carbon economic dispatch strategy for integrated electrical and gas system with GCCP based on multi-agent deep reinforcement learning by Feng, Wentao, Deng, Bingyan, Zhang, Ziwen, Jiang, He, Zheng, Yanxi, Peng, Xinran, Zhang, Le, Jing, Zhiyuan

“…With the growing concern for the environment, sustainable development centred on a low-carbon economy has become a unifying pursuit for the energy industry…”
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Optimizing Maritime Energy Efficiency: A Machine Learning Approach Using Deep Reinforcement Learning for EEXI and CII Compliance by Alshareef, Mohammed H., Alghanmi, Ayman F.

“…The International Maritime Organization (IMO) has set stringent regulations to reduce the carbon footprint of maritime transport, using metrics such as the…”
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