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2020 – today
- 2025
[i2]Changhua Pei, Zexin Wang, Fengrui Liu, Zeyan Li, Yang Liu, Xiao He, Rong Kang, Tieying Zhang, Jianjun Chen, Jianhui Li, Gaogang Xie, Dan Pei:
Flow-of-Action: SOP Enhanced LLM-Based Multi-Agent System for Root Cause Analysis. CoRR abs/2502.08224 (2025)- 2024
- [j6]Yuanzhen Zhang
, Wenbo Li, Fengrui Liu, Pengtao Chen, Haomin Zhu, Hai Li, Guorui Li, Kai Tao, Wen-Ming Zhang, Jian Xu:
A Manta Ray-Inspired Fast-Swimming Soft Electrohydraulic Robotic Fish. IEEE Robotics Autom. Lett. 9(9): 8043-8050 (2024) - [j5]Zhengyan Zhang, Xiaodong Qu, Wolin Li, Hongzhe Miao, Fengrui Liu:
DOA Estimation Method Based on Unsupervised Learning Network With Threshold Capon Spectrum Weighted Penalty. IEEE Signal Process. Lett. 31: 701-705 (2024) - 2023
- [j4]Lijun Yang, Xiaoge Wei, Fengrui Liu, Xiangru Zhu, Feng Zhou:
Automatic feature learning model combining functional connectivity network and graph regularization for depression detection. Biomed. Signal Process. Control. 82: 104520 (2023) - [j3]Fengrui Liu, Yang Wang, Zhenyu Li, Hongtao Guan, Gaogang Xie:
AD2S: Adaptive anomaly detection on sporadic data streams. Comput. Commun. 209: 151-162 (2023) - [c8]Rui Ren, Yang Wang, Fengrui Liu, Zhenyu Li, Gareth Tyson, Tianhao Miao, Gaogang Xie:
Grace: Interpretable Root Cause Analysis by Graph Convolutional Network for Microservices. IWQoS 2023: 1-4 - [c7]Rui Ren, Yang Wang, Fengrui Liu, Zhenyu Li, Gaogang Xie:
Triple:The Interpretable Deep Learning Anomaly Detection Framework based on Trace-Metric-Log of Microservice. IWQoS 2023: 1-10 - 2022
- [c6]Fengrui Liu, Yang Wang, Zhenyu Li, Rui Ren, Hongtao Guan, Xian Yu, Xiaofan Chen, Gaogang Xie:
MicroCBR: Case-Based Reasoning on Spatio-temporal Fault Knowledge Graph for Microservices Troubleshooting. ICCBR 2022: 224-239 - [d1]Fengrui Liu:
AD2S experiments. IEEE DataPort, 2022
- 2021
- [j2]Fengrui Liu, Yang Li, Baitong Li, Jiaxin Li, Huiyang Xie:
Bitcoin transaction strategy construction based on deep reinforcement learning. Appl. Soft Comput. 113(Part): 107952 (2021) - [c5]Yixin Wang, Fengrui Liu, Lijun Yang:
EEG-Based Depression Recognition Using Intrinsic Time-scale Decomposition and Temporal Convolution Network. BIBE 2021: 5:1-5:6 - [c4]Fengrui Liu, Xuefei Li, Wei Xiong, Haiyang Jiang, Gaogang Xie:
An Accuracy Network Anomaly Detection Method Based on Ensemble Model. ICASSP 2021: 8548-8552 - [c3]Fengrui Liu, Haiyang Jiang, Zulong Diao, Yanbiao Li, Gaogang Xie:
CyCo: A Temporal Cycle Consistency Based Labeling Method for Time Series Data. IJCNN 2021: 1-8 - [c2]Wei Xiong, Haiyang Jiang, Hongtao Guan, Fengrui Liu:
DSQNet: Domain SeQuence based Deep Neural Network for AGDs Detection. ISCC 2021: 1-7 - [i1]Fengrui Liu, Yang Li, Baitong Li, Jiaxin Li, Huiyang Xie:
Bitcoin Transaction Strategy Construction Based on Deep Reinforcement Learning. CoRR abs/2109.14789 (2021)
2010 – 2019
- 2019
- [j1]Ke Xu, Jianxin Liu, Jun Miao, Fengrui Liu:
An improved SIFT algorithm based on adaptive fractional differential. J. Ambient Intell. Humaniz. Comput. 10(8): 3297-3305 (2019) - 2017
- [c1]Fengrui Liu, Chuanhe Huang, Xiying Fan:
A Topology-Aware Reliable Broadcast Scheme for Multidimensional VANET Scenarios. CollaborateCom 2017: 275-285
Coauthor Index
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