中南大学 wangjing

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王劲

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[1]Position-track-time three-dimensional network model-based improvement for high-speed rail scheduling and operation[J].Computer-Aided Civil and Infrastructure Engineering, 2022, 38 (6) : 720-738.
[2]Target-free recognition of cable vibration in complex backgrounds based on computer vision[J].Mechanical Systems and Signal Processing, 2023, 197
[3]Research on the Application of Fuzzy Bayesian Network in Risk Assessment of Catenary Construction[J].Mathematics, 2023, 11: 1719.
[4]Optimizing High-Speed Railroad Timetable with Passenger and Station Service Demands: A Case Study in the Wuhan-Guangzhou Corridor[J].Journal of Advanced Transportation, 2018
[5]Column Generation Accelerated Algorithm and Optimisation for a High-Speed Railway Train Timetabling Problem[J].Symmetry, 2019, 11: 983.
[6]Hybrid pixel-level crack segmentation for ballastless track slab using digital twin model and weakly supervised style transfer[J].Structural Control and Health Monitoring, 2024
[7]A Multistation 3D Point Cloud Automated Global Registration and Accurate Positioning Method for Railway Tunnels[J].Structural Control and Health Monitoring, 2023
[8]Fine-Grained Point Cloud Semantic Segmentation of Complex Railway Bridge Scenes from UAVs Using Improved DGCNN[J].Structural Control and Health Monitoring, 2023
[9]Intelligent paving and compaction technologies for asphalt pavement[J].Automation in Construction, 2023, 156: 105081.
[10]Machine vision-based surface crack analysis for transportation infrastructure[J].Automation in Construction, 2021
[11]Accelerating column generation strategies for high-speed railway train timetabling problem from low-carbon and environmentally-friendly transport perspective[J].Journal of Environmental Protection and Ecology, 2019
[12]基于改进MIP模型的铁路牵引供电系统维护决策优化[J].中南大学学报自然科学版, 2023, 54 (11) : 4551-4560.
[13]基于因果贝叶斯网络的接触网风险评估模型研究[J].铁道科学与工程学报, 2023, 20 (8) : 3061-3071.
[14]基于多目标级联深度学习的无砟轨道板表面裂缝测量[J].铁道科学与工程学报, 2023, 20 (9) : 3592-3603.
[15]基于集成深度学习的钢轨表面伤损精细化分割[J].铁道工程学报, 2023, 40 (7) : 27.
[16]基于深度联合学习的复杂背景条件下 CRTSⅡ型板式无砟轨道结构表面裂缝自动化检测.京沪高铁运营10周年学术论文集, 2022
[17]基于改进形状匹配的扣件缺陷检测方法[J].铁道科学与工程学报, 2022
[18]基于深度学习和虚拟模型的路面全域伤损状态自动化感知[J].中国公路学报, 2023, 36 (3) : 61-69.
[19]高铁四电建设工程信息共享演化博弈分析[J].铁道科学与工程学报, 2023, 20 (1) : 44-52.
[20]基于深度风格迁移合成数据的扣件异常状态检测[J].铁道学报, 2023

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