舒小颂
郑州大学水利与交通学院副研究员
研究方向：水利工程智能安全监测结构健康诊断与人工智能融合方法
办公地点：
个人简介
舒小颂，郑州大学水利与交通学院副研究员，主要研究方向为水利工程智能安全监测、结构健康诊断与人工智能融合方法，包括深度学习异常检测、时空变分自编码器、多源信息融合、知识图谱等。作为核心骨干参与国家重点研发计划项目课题“黄河上游干流库坝群多灾种应对关键技术(2022YFC3004402)”子课题、河南省重点研发专项项目“极端自然灾害下黄河梯级水库群多目标监测预警及智能化应急预演体系研究(221111321100)”子课题。
在水利大坝安全评估领域，在Computer-Aided Civil and Infrastructure Engineering、Automation in Construction、Advanced Engineering Informatics等权威期刊发表SCI论文20余篇，授权发明专利2项。研究成果涵盖大坝安全评价、裂缝智能识别与量化等关键技术，服务于混凝土坝、隧洞等水工结构的安全监控。同时，作为技术骨干完成中国铁路郑州局集团有限公司重点课题“国内通用基础人工智能大模型在铁路应用场景探索”，构建铁路领域知识图谱系统，形成软件著作权1项及发明专利1项。担任Automation in Construction、Advanced Engineering Informatics、Engineering Structures、Mechanical Systems and Signal Processing等国际期刊审稿人。
论文和专著
【论文】
[1] Shu Xiaosong*, Yang Haibo, Zhou Yuhang, Xu Peng, Liu Xinyi, Guo Jinjun, Cai Yingchun, Fan Jingyu, Fan Wu. Ontology-driven intelligent assessment system for dam structural safety based on spatiotemporal anomaly detection framework[J]. Computer-Aided Civil and Infrastructure Engineering, 2025, 40(29): 5649-5671. (中科院一区TOP，郑大TOP期刊)
[2] Shu Xiaosong, Yang Haibo, Wu Fan, Zhou Yuhang, Xu Peng, Liu Xinyi, Guo Jinjun, Cai Yingchun, Fan Jinyu. An integrated spatiotemporal trust and consensus fusion framework for dam safety assessment with multi-sensor anomaly detection[J]. Computer-Aided Civil and Infrastructure Engineering, 2025, 40(29): 5625-5648. (中科院一区TOP，郑大TOP期刊)
[3]Shu Xiaosong, Bao Tengfei*, Xu Ruichen, Li Yangtao, Zhang Kang. Dam anomaly assessment based on sequential variational autoencoder and evidence throry[J]. Applied Mathematical Modelling, 2021, 98: 574-594. (中科院一区TOP)
[4] Chen Xudong, Li Liuyang, Lu Qinghe, Liu Caiyu, Guo Jinjun, Shu Xiaosong*, Li Bo, Gu Chongshi. Considering the spatiotemporal association characteristics of multiple monitoring points: A deformation prediction framework for high arch dams during the initial operation period[J]. Advanced Engineering Informatics, 2026, 73:104559. (中科院一区TOP)
[5] Shu Xiaosong, Bao Tengfei*, Li Yangtao, Gong Jian, Zhang Kang. VAE-TALSTM: a temporal attention and variational autoencoder-based long short-term memory framework for dam displacement prediction[J]. Engineering with Computers, 2022, 38: 3497-3512. (中科院二区TOP)
[6] Shu Xiaosong, Bao Tengfei*, Zhou Yuhang,Xu Ruichen, Li Yangtao, Zhang Kang. Unsupervised dam anomaly detection with the spatial-temporal variational autoencoder[J]. Structural Health Monitoring, 2022, 22(1): 39-55.
[7] Zhou Yuhang, Shu Xiaosong*, Bao Tengfei, Li Yangtao, Zhang Kang. Dam safety assessment through data-level anomaly detection and information fusion[J]. Structural Health Monitoring, 2023, 22(3): 2002-2021.
[8] Shu Xiaosong, Bao Tengfei*, Li Yangtao, Zhang Kang, Wu Bangbin. Dam safety evaluation based on interval-valued intuitionistic fuzzy sets and evidence theory[J]. Sensors, 2020, 20(9): 2468.
[9] Shu Xiaosong, Bao Tengfei*, Hu Yuhan, Li Yangtao, Zhang Kang. Camera calibration method using synthetic speckle pattern with an improved gray wolf optimizer algorithm[J]. Applied Optics, 2021, 60(34): 10477-10489.
[10] Yang Haibo, Huang Jiaqi, Liu Xinyi, Xu Peng, Yu Bo, Guo Jinjun, Li Junhua, Zhou Yuhang, Shu Xiaosong*. Integration of Morris and GLUW methods for improving massflow-based debris floe simulation[J]. Natural Hazards, 2025, 121(11): 12589-12612.
[11] Zhou Yuhang, Bao Tengfei*, Shu Xiaosong, Li Yangtao, Zhang Kang. BIM and ontology-based knowledge management for dam safety monitoring[J]. Automation in Construction, 2023, 145: 104649.
[12] Zhou Yuhang, Bao Tengfei*, Li Guiyue, Shu Xiaosong, Li Yangtao, Zhang Kang. Multi-expert attention network for long-term dam displacement prediction[J]. Advanced Engineering Informatics, 2023, 57(11): 102060.