5篇
您的检索式：作者名="FENG Mingxiao"
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| 1 | Two new triterpenoid saponins from the root of Ilex pubescens显示文摘 | FENG Feng ZHU Mingxiao XIE Ning | 2008 | J Asian Nat Prod Res2008，10，1： | 1 |
| 2 | Electrochemical fabrication of polythiophene film coated metallic nanowire arrays显示文摘 | Jiaxin Zhang Gaoquan Shi Chen Liu Liangti Qu Mingxiao Fu Feng’en Chen | 2003 | Journal of Materials Science2003，，11： | 1 |
| 3 | Raman spectroscopic evidence of thickness dependence of the doping level of electrochemically deposited polypyrrole film 显示文摘 | Chen Feng' en Shi Gaoquan Fu Mingxiao | 2003 | Synth Met2003，132，2： | 1 |
| 4 | Raman spectroscopic studies on the structural changes of poly(3-methylthiophene) during heating and cooling processes显示文摘Poly(3-methylthiophene) (PMeT) electrosyn-thesized by direct oxidation of 3-methylthiophene in boron trifluoride diethyl etherate (BFEE) has been studied by Raman spectroscopy in the temperature scale of 123-458 K. Experimental results demonstrate that the thermal stability of PMeT in the oxidized state is much lower than that of the polymer in the neutral state. Furthermore, during the cooling process, the conformation of neutral species changes from a coil-like state into a rod-like state, while the conformation of the oxidized species does not change. | CHEN Feng’en ZHANG Jiaxin FU Mingxiao SHI Gaoquan | 2002 | Chinese Science Bulletin2002，47，21： | 0 |
| 5 | Multi-Agent Hierarchical Graph Attention Reinforcement Learning for Grid-Aware Energy Management显示文摘The increasing adoption of renewable energy has posed challenges for voltage regulation in power distribution networks.Gridaware energy management,which includes the control of smart inverters and energy management systems,is a trending way to mitigate this problem.However,existing multi-agent reinforcement learning methods for grid-aware energy management have not sufficiently considered the importance of agent cooperation and the unique characteristics of the grid,which leads to limited performance.In this study,we propose a new approach named multi-agent hierarchical graph attention reinforcement learning framework(MAHGA)to stabilize the voltage.Specifically,under the paradigm of centralized training and decentralized execution,we model the power distribution network as a novel hierarchical graph containing the agent-level topology and the bus-level topology.Then a hierarchical graph attention model is devised to capture the complex correlation between agents.Moreover,we incorporate graph contrastive learning as an auxiliary task in the reinforcement learning process to improve representation learning from graphs.Experiments on several real-world scenarios reveal that our approach achieves the best performance and can reduce the number of voltage violations remarkably. | FENG Bingyi FENG Mingxiao WANG Minrui ZHOU Wengang LI Houqiang | 2023 | ZTE Communications2023，21，3： | 0 |
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