2024 |2023 |2022 | 2021 | 2020 | 2019 | 2018

2024

[1] Xue B, Gao M, Wang C, et al. Crowd-Aware Socially Compliant Robot Navigation via Deep Reinforcement Learning[J]. International Journal of Social Robotics, 2024, 16(1): 197-209.

2023

[1] Liu J, Wang G X, Fan C F, et al. Question-conditioned debiasing with focal visual context fusion for visual question answering[J]. Knowledge-Based Systems, 2023: 110879.

[2] Jin Liu, ChongFeng Fan, FengYu Zhou*, HuiJuan Xu. Be flexible! learn to debias by sampling and prompting for robust visual question answering[J]. Information Processing & Management, 2023, 60(3): 103296.

[3] Lei Yin, Jin Liu, Yadong Fang, Ming Gao, Ming Li and Fengyu Zhou*. Two‑stage hybrid genetic algorithm for robot cloud service selection[J]. Journal of Cloud Computing:Advances Systems and Applications, (2023) 12:95.

[4] Lei Yin, Chang Sun, Ming Gao, Yadong Fang, Ming Li and Fengyu Zhou*. Hyper-Heuristic Task Scheduling Algorithm Based on Reinforcement Learning in Cloud Computing [J]. Intelligent Automation & Soft Computing, 2023, 37(2):1587-1608.

[5] Yin L, Liu J, Zhou F, et al. Cost-based hierarchy genetic algorithm for service scheduling in robot cloud platform[J]. Journal of Cloud Computing, 2023, 12(1): 1-16.

[6] Zhang L, Miao Z, et al. Fault Diagnosis for Mobile Robots Based on Spatial-temporal Graph Attention Network Under Imbalanced Data[J]. IEEE Transactions on Instrumentation and Measurement, 2023.

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.

[5] Liu J, Fan C, Fengyu Z, et al. Syntax Controlled Knowledge Graph-to-Text Generation with Order and Semantic Consistency[C]//Findings of the Association for Computational Linguistics: NAACL 2022. 2022: 1278-1291.

[6] Meizhen Liu, FengYu Zhou, JiaKai He, Ke Chen, Yang Zhao, and HongChang Sun. 2022. Self-Attention Networks and Adaptive Support Vector Machine for aspect-level sentiment classification. Soft Comput. 26, 18 (Sep 2022), 9621–9634.

[7] Y. Wang, M. Yao, C. Sun and F. Zhou, “Iterative learning control for conformable fractional order system with time delay,” 2022 12th International Conference on CYBER Technology in Automation, Control, and Intelligent Systems (CYBER), 2022, pp. 129-133, doi: 10.1109/CYBER55403.2022.9907195.

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.