云基智能机器人实验室

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2022 | 2021 | 2020 | 2019 | 2018

2022

[1] Z. Miao, Y. Xia, F. Zhou and X. Yuan, “Fault Diagnosis of Wheeled Robot Based on Prior Knowledge and Spatial-temporal Difference Graph Convolutional Network,” in IEEE Transactions on Industrial Informatics, 2022, doi: 10.1109/TII.2022.3208001.

[2] Meizhen Liu, Fengyu Zhou, Jiakai He, Xiaohui Yan,Knowledge graph attention mechanism for distant supervision neural relation extraction,Knowledge-Based Systems, 2022, 109800. DOI:10.1016/j.knosys.2022.109800.

[3] Miao Z, Zhou F, Yuan X, et al. Multi-heterogeneous sensor data fusion method via convolutional neural network for fault diagnosis of wheeled mobile robot[J]. Applied Soft Computing, 2022: 109554.DOI:10.1016/j.asoc.2022.109554.

[4] CHEN K, XUE B, ZHANG M, et al. An Evolutionary Multitasking-Based Feature Selection Method for High-Dimensional Classification[J/OL]. IEEE Transactions on Cybernetics, 2022, 52(7): 7172-7186. DOI:10.1109/TCYB.2020.3042243.

2021

[1] CHEN K, XUE B, ZHANG M, et al. Evolutionary Multitasking for Feature Selection in High-Dimensional Classification via Particle Swarm Optimization[J/OL]. IEEE Transactions on Evolutionary Computation, 2022, 26(3): 446-460. DOI:10.1109/TEVC.2021.3100056.

[2] FENGYU Z, YUGANG W. Iterative learning control for fractional order nonlinear system with initial shift[J/OL]. Nonlinear Dynamics, 2021, 106(4): 3305-3314. DOI:10.1007/s11071-021-06932-z.

[3] SUN H, ZHAI W, WANG Y, et al. Privileged information-driven random network based non-iterative integration model for building energy consumption prediction[J/OL]. Applied Soft Computing, 2021, 108: 107438. DOI:10.1016/j.asoc.2021.107438.

[4] WANG Y, ZHOU F, YIN L, et al. Iterative Learning Control for Fractional Order Linear Systems with Time Delay Based on Frequency Analysis[J/OL]. International Journal of Control, Automation and Systems, 2021, 19(4): 1588-1596. DOI:10.1007/s12555-019-0295-y.

[5] LIU M, ZHOU F, CHEN K, et al. Co-attention networks based on aspect and context for aspect-level sentiment analysis[J/OL]. Knowledge-Based Systems, 2021, 217: 106810. DOI:10.1016/j.knosys.2021.106810.

[6] HUANG Q, ZHOU F, QIN R, et al. View transform graph attention recurrent networks for skeleton-based action recognition[J/OL]. Signal, Image and Video Processing, 2021, 15(3): 599-606. DOI:10.1007/s11760-020-01781-6.

[7] SUN H, WANG Y, NIU L, et al. A novel fuzzy rough set based long short-term memory integration model for energy consumption prediction of public buildings[J/OL]. Journal of Intelligent & Fuzzy Systems, 2021, 40(3): 5715-5729. DOI:10.3233/JIFS-201857.

[8] SUN H, WANG S, ZHOU F, et al. Dynamic Deployment and Scheduling Strategy for Dual-Service Pooling Based Hierarchical Cloud Service System in Intelligent Buildings[J/OL]. IEEE Transactions on Cloud Computing, 2021: 1-1. DOI:10.1109/TCC.2021.3078795.

[9] CHEN K, XUE B, ZHANG M, et al. Correlation-Guided Updating Strategy for Feature Selection in Classification with Surrogate-Assisted Particle Swarm Optimisation[J/OL]. IEEE Transactions on Evolutionary Computation, 2021: 1-1. DOI:10.1109/TEVC.2021.3134804.

[10] 缪昭明, 袁宪锋, 张晖, 等.基于SE-CNN的服务机器人运动系统云端故障诊断方法[J/OL]. 机器人, 2021, 43(3): 321-330. DOI:10.13973/j.cnki.robot.200295.

2020

[1] YUGANG W, FENGYU Z, YANG Z, et al. Iterative learning control for path tracking of service robot in perspective dynamic system with uncertainties[J/OL]. International Journal of Advanced Robotic Systems, 2020, 17(6): 172988142096852. DOI:10.1177/1729881420968528.

[2] GU P, ZHOU F, YU D, et al. A 3D Reconstruction Method Using Multisensor Fusion in Large-Scale Indoor Scenes[J/OL]. Complexity, 2020, 2020:1-14. DOI:10.1155/2020/6973790.

[3] HUANG Q, ZHOU F, HE J, et al. Spatial–temporal graph attention networks for skeleton-based action recognition[J/OL]. Journal of Electronic Imaging, 2020, 29(05)[2022-09-01]. https://www.spiedigitallibrary.org/journals/journal-of-electronic-imaging/volume-29/issue-05/053003 Spatialtemporal-graph-attention-networks-for-skeleton-based-action-recognition/10.1117/1.JEI.29.5.053003.full. DOI:10.1117/1.JEI.29.5.053003.

[4] ZHUANG W, ZHOU F, WAN F, et al. Cloud-based real-time collaborative mapping and merging method for multi-robot with landmark information[C/OL]//2020 Chinese Control And Decision Conference (CCDC). Hefei, China: IEEE, 2020: 4319-4324[2022-09-01]. https://ieeexplore.ieee.org/document/9164732/. DOI:10.1109/CCDC49329.2020.9164732.

[5] CHEN K, XUE B, ZHANG M, et al. Hybridising Particle Swarm optimisation with Differential Evolution for Feature Selection in Classification[C/OL]//2020 IEEE Congress on Evolutionary Computation (CEC). Glasgow, United Kingdom: IEEE, 2020: 1-8[2022-09-01]. https://ieeexplore.ieee.org/document/9185533/. DOI:10.1109/CEC48606.2020.9185533.

[6] CHEN K, XUE B, ZHANG M, et al. Novel chaotic grouping particle swarm optimization with a dynamic regrouping strategy for solving numerical optimization tasks[J/OL]. Knowledge-Based Systems, 2020, 194: 105568. DOI:10.1016/j.knosys.2020.105568.

[7] LIU X, ZHOU F, LIU J, et al. Meta-Learning based prototype-relation network for few-shot classification[J/OL]. Neurocomputing, 2020, 383: 224-234. DOI:10.1016/j.neucom.2019.12.034.

[8] 周风余, 庄文密, 万方, 等.基于路标与云架构的多机器人建图及融合方法[J/OL]. 华中科技大学学报(自然科学版), 2020,48(11): 30-36. DOI:10.13245/j.hust.201105.

[9] 黄晴晴, 周风余, 刘美珍. 基于视频的人体动作识别算法综述[J/OL]. 计算机应用研究, 2020, 37(11): 3213-3219. DOI:10.19734/j.issn.1001-3695.2019.08.0253.

2019

[1] CHEN K, ZHOU F Y, YUAN X F. Hybrid particle swarm optimization with spiral-shaped mechanism for feature selection[J/OL]. Expert Systems with Applications, 2019, 128: 140-156. DOI:10.1016/j.eswa.2019.03.039.

[2] LIU J, ZHOU F, YIN L. Design of a Service Robot Cloud Service Platform[C/OL]//2019 4th Asia-Pacific Conference on Intelligent Robot Systems (ACIRS). Nagoya, Japan: IEEE, 2019:124-128[2022-09-01]. https://ieeexplore.ieee.org/document/8936034/. DOI:10.1109/ACIRS.2019.8936034.

[3] YUAN X, LIU Z, MIAO Z, et al. Fault Diagnosis of Analog Circuits Based on IH-PSO Optimized Support Vector Machine[J/OL]. IEEE Access, 2019, 7: 137945-137958. DOI:10.1109/ACCESS.2019.2943071.

[4] LIU J, ZHOU F, YIN L, et al. A Novel Cloud Platform for Service Robots[J/OL]. IEEE Access, 2019, 7: 182951-182961. DOI:10.1109/ACCESS.2019.2927743.

[5] 周风余, 万方, 焦建成, 等.家庭陪护机器人自主充电系统研究与设计[J]. 山东大学学报(工学版), 2019, 49(1): 55-65+74.

[6] 尹磊, 周风余, 李铭, 等.基于微服务的服务机器人云服务设计方法[J]. 山东大学学报(工学版), 2019, 49(6): 55-62+80.

[7] 万方, 周风余, 尹磊, 等.基于电势场法的移动机器人全局路径规划算法[J/OL]. 机器人, 2019, 41(6): 742-750. DOI:10.13973/j.cnki.robot.180687.

[8] 刘美珍, 周风余, 李铭, 等.基于模型不确定补偿的轮式移动机器人反演复合控制[J]. 山东大学学报(工学版), 2019, 49(6): 36-44.

[9] 常致富, 周风余, 王玉刚, 等.基于深度学习的图像自动标注方法综述[J]. 山东大学学报(工学版), 2019, 49(6): 25-35.

2018

[1] CHEN K, ZHOU F, WANG Y, et al. An ameliorated particle swarm optimizer for solving numerical optimization problems[J/OL]. Applied Soft Computing, 2018, 73: 482-496. DOI:10.1016/j.asoc.2018.09.007.

[2] CHEN K, ZHOU F, XUE B. Particle Swarm Optimization for Feature Selection with Adaptive Mechanism and New Updating Strategy[M/OL]//MITROVIC T, XUE B, LI X. AI 2018: Advances in Artificial Intelligence: 卷 11320. Cham: Springer International Publishing, 2018: 419-431[2022-09-01]. http://link.springer.com/10.1007/978-3-030-03991-2_39. DOI:10.1007/978-3-030-03991-2_39.

[3] 沈冬冬, 周风余, 栗梦媛, 等.基于集成深度神经网络的室内无线定位[J]. 山东大学学报(工学版), 2018, 48(5): 95-102.