International Journal of Digital Earth (Dec 2020)

The construction of personalized virtual landslide disaster environments based on knowledge graphs and deep neural networks

  • Yunhao Zhang,
  • Jun Zhu,
  • Qing Zhu,
  • Yakun Xie,
  • Weilian Li,
  • Lin Fu,
  • Junxiao Zhang,
  • Jianmei Tan

DOI
https://doi.org/10.1080/17538947.2020.1773950
Journal volume & issue
Vol. 13, no. 12
pp. 1637 – 1655

Abstract

Read online

Virtual Landslide Disaster environments are important for multilevel simulation, analysis and decision-making about Landslide Disasters. However, in the existing related studies, complex disaster scene objects and relationships are not deeply analyzed, and the scene contents are fixed, which is not conducive to meeting multilevel visualization task requirements for diverse users. To resolve the above issues, a construction method for Personalized Virtual Landslide Disaster Environments Based on Knowledge Graphs and Deep Neural networks is proposed in this paper. The characteristics of relationships among users, scenes and data were first discussed in detail; then, a knowledge graph of virtual Landslide Disaster environments was established to clarify the complex relationships among disaster scene objects, and a Deep Neural network was introduced to mine the user history information and the relationships among object entities in the knowledge graph. Therefore, a personalized Landslide Disaster scene data recommendation mechanism was proposed. Finally, a prototype system was developed, and an experimental analysis was conducted. The experimental results show that the method can be used to recommend intelligently appropriate disaster information and scene data to diverse users. The recommendation accuracy stabilizes above 80% – a level able to effectively support The Construction of Personalized Virtual Landslide Disaster environments.

Keywords