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Lingzhi Yin and Yafei Wang
Delving into the spatiotemporal evolution of the railway network in different periods can provide guidance and reference for the planning and layout of the railway network. However, most of the existing studies tended to model the railway data separately...
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Lingzhi Yin, Jun Zhu, Wenshu Li and Jinhong Wang
As the passenger railway network is expanding and improving, the internal connections and interdependence in the network are rising. Once a sudden geological hazard occurs and damages the network structure, the train service is prone to large-scale halt ...
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Lin Fu, Jun Zhu, Jianbo Lai, Weilian Li, Pei Dang, Lingzhi Yin, Jialuo Li, Yukun Guo and Jigang You
The rapid acquisition of deposit volume information and dynamic modeling, as well as the visualization of disaster scenes, have great significance for the sharing of landslide information and the management of emergency rescue. However, existing methods ...
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Lingzhi Yin and Yafei Wang
The internal structure and operation rules of railway network have become increasingly complex along with the expansion of the network, putting a higher demand on the development of the railway and the reliability and adaptability of the railway under ea...
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Yunhao Zhang, Jun Zhu, Weilian Li, Qing Zhu, Ya Hu, Lin Fu, Junxiao Zhang, Pengcheng Huang, Yakun Xie and Lingzhi Yin
The construction of a virtual debris flow disaster environment is of great significance in debris flow disaster prevention, risk assessment, accurate simulation, and disaster emergency response. However, existing research on virtual disaster environments...
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Weilian Li, Jun Zhu, Yunhao Zhang, Yungang Cao, Ya Hu, Lin Fu, Pengcheng Huang, Yakun Xie, Lingzhi Yin and Bingli Xu
Scientific and appropriate visualizations increase the effectiveness and readability of disaster information. However, existing fusion visualization methods for disaster scenes have some deficiencies, such as the low efficiency of scene visualization and...
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Lingzhi Yin, Jun Zhu, Yi Li, Chao Zeng, Qing Zhu, Hua Qi, Mingwei Liu, Weilian Li, Zhenyu Cao, Weijun Yang and Pengcheng Zhang
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