1.学术著作 [1] 周伟,高鹏,易军.无线传感器网络定位跟踪算法研究[M]. 北京理工大学出版社,2020.12. 2.代表性学术论文 [1] Wei Zhou, Honggang Li, Li Zheng, Shan Xiao, Jun Yi. A Lightweight Detection and Recognition Framework for cigarette laser code. Engineering Applications of Artificial Intelligence. Volume 160, Part A, 15 November 2025, 111777. (中科院SCI一区) [2] Wei Zhou, HaiHang Zhao, XiangChengZhen Li, ZhongLi Qi, Fuqiang Lai, Jun Yi. Missing well logs reconstruction based on cascaded bidirectional long short-term memory network. Expert Systems with Applications. Vol. 259, January 2025, 125270. (中科院SCI一区) [3] Wei Zhou, Xiangchengzhen Li, ZhongLi Qi, HaiHang Zhao, Jun Yi. A shale gas production prediction model based on masked convolutional neural network. Applied Energy. 353: 122092, 2024.(中科院SCI一区) [4] Wei Zhou, Fujian Zheng, Yiheng Zhao, Yiran Pang, Jun Yi. MSDCNN: A multiscale dilated convolution neural network for fine-grained 3D shape classification. Neural Networks. 106141, 2024. (中科院SCI一区) [5] Wei Zhou, Yiheng Zhao, Yi Xiao, Xuanlin Min, Jun Yi. TNPC: Transformer-based network for point cloud classification. Expert Systems with Applications. 239:122438, 2024. (中科院SCI一区) [6] Xuanlin Min, Wei Zhou*, Rui Hu, Yinyue Wu, Yirang Pang and Jun. Yi. LWUAVDet: A Lightweight UAV Object Detection Network on Edge Devices. IEEE Internet of Things Journal, 11(13):24013-24023, 2024(中科院SCI一区) [7] Wei Zhou, Li Zheng, Xiangchengzhen Li, Zaidao Yang, Jun Yi. CLCRNet: An Optical Character Recognition Network for Cigarette Laser Code, IEEE Transactions on Instrumentation and Measurement,, 2024.(中科院SCI二区) [8] Wei Zhou, Fujian Zheng, Gang Yin, Yiran Pang, Jun Yi. YOLOTrashCan: A Deep Learning Marine Debris Detection Network. IEEE Transactions on Instrumentation and Measurement, 72:1-12, 2023.(中科院SCI二区) [9] Wei Zhou, Xuanlin Min, Yiheng Zhao, Yiran Pang, Jun Yi. A Multi-Scale Spatio-Temporal Network for Violence Behavior Detection. IEEE Transactions on Biometrics, Behavior, and Identity Science, 5(2):266-276, 2023. [10] Jun Yi, Zhilong Shen, Fan Chen, Yiheng Zhao, Shan Xiao, Wei Zhou*. A Lightweight MultiScale Feature Fusion Network for Remote Sensing Object Counting, IEEE Transactions on Geoscience and Remote Sensing, vol.61, 2023 (中科院一区,IF= 8.2) [11] 周伟,赵海航,蒋云凤,易军,赖富强.基于串级双向长短时记忆神经网络的测井数据重构.石油地球物理勘探,2022, 57(6):1373-1380. [12] Wei Zhou, Jun Yi, Lizhong Yao, Guorong Chen. Event-Triggered Optimal Control for the Continuous Stirred Tank Reactor System. IEEE Transactions on Artificial Intelligence, 3(2):228-237, 2022. [13] Jun Yi, Wei Zhang, Junren Bai, Wei Zhou*. Multifactorial Evolutionary Algorithm Based on Improved Dynamical Decomposition for Many-objective Optimization Problems. IEEE Transactions on Evolutionary Computation, 26(2) :334-348, 2022. (中科院SCI一区) [14] Wei Zhou, Huachao Liu, Haibo He, Jun Yi. Neuro-Optimal Tracking Control for Continuous Stirred Tank Reactor With Input Constraints. IEEE Transactions on Industrial Informatics, 15(8): 4516-4524, 2019. (中科院SCI一区) [15] Wei Zhou, Xiaoliang Li, Jun Yi, Haibo He. A Novel UKF-RBF Method Based on Adaptive Noise Factor for Fault Diagnosis in Pumping Unit. IEEE Transactions on Industrial Informatics, 15(3): 1415-1424, 2019. (中科院SCI一区) 3.授权发明专利 [1] 周伟,邓粤鹏,闵宣霖等,一种便携式异常行为智能分析系统[P].ZL202111268194.X,2024.12 [2] 周伟,汪波,钱龙等,一种基于全相关动态KPLS的故障诊断方法[P]. ZL201911048863.5,2023.03 [3] 周伟,郑福建,郭鑫,庞一然等. 一种基于监控视频的遗留物检测方法[P]. ZL202010874464.0,2022.04 [4] 周伟,李晓亮,刘华超等,基于自适应无迹Kalman滤波与RBF神经网络的抽油机故障诊断方法[P]. ZL201710283330.X, 2021.09 [5] 周伟,刘华超,汪波等,基于UKF与ADDHP的天然气吸收塔脱硫过程控制方法[P]. ZL201711115683.5,2021.01 [6] 周伟,甘丽群,周盼,刘华超等,基于welch多段平均功率谱法的油井动液面深度检测方法[P]. ZL201710331208.5,2020.06 [7] 周伟,刘华超,甘丽群等,基于RBF与ADHDP的天然气吸收塔脱硫过程控制方法[P]. ZL201711117446.2,2020.10 [8] 周伟,李家庆,白俊仁等.基于物联网大数据分析的植物栽培方法及系统[P]. ZL201610883950.2,2019.07 [9] 周伟,周盼,李晓亮等.用于油井动液面检测的频率估算方法, 中国[P]. ZL201610177653.6,2019.03 [10] 周伟,刘娟,李太福等.油井动液面深度测量装置的测量方法[P]. ZL201410556923.5,2018.06. [11] 周伟,许奎,李太福等.用于油井动液面深度检测的声音信号处理方法[P]. ZL201410059106.9,2017.3. [12] 周伟,贾威,李太福,郭小渝,廖志强,姚立忠.油井动液面深度检测方法及装置[P]. ZL201310255054.8,2016.4. 4.科技奖励 [1] 复杂油井动液面监测关键技术及应用,重庆市科技进步奖二等奖,2022. [2] 通风瓦斯参数移动互联精准采集融合分析关键技术及系统,重庆市技术发明二等奖,2024. [3] 多能协同供应和能源综合梯级利用集成技术与应用,重庆市科技进步奖三等奖,2020. 5.联系方式 招生信息:课题组与国内外知名高校、研究机构及IT企业合作紧密,欢迎计算机、软件、智科及数学等相关专业同学申请加入课题组。 课题组公众号:智能计算与模式识别科技创新团队 https://mp.weixin.qq.com/s/6I0fwspUBc9sSjFLJVVfSw |