摘要
为深入了解自然灾害应急管理的实际需求和现状,运用4R模型和人工智能语言模型,利用弱监督LDA的方式分析2013—2022年间CNKI数据库中自然灾害应急管理领域的文献,揭示各年主题热度及演化趋势。研究发现:已有研究主要集中于“应急预案与规划”“灾害预警系统”等方面,其中“灾情监测与评估”成为显著热点。随时间推移,“恢复重建”关注度逐渐降低,“灾害风险识别与评估”受到更多关注。自然灾害应急管理的研究从关注应急管理方法、技术、策略的应用和效果,正在逐渐转向关注灾害的全周期综合管理和长期恢复。在关口前置背景下,需要推进全周期应急管理,深化核心研究和优化薄弱环节。
In order to deeply understand the actual needs and current situation of natural disaster emergency management,4R model and artificial intelligence language model are applied to analyze the literature in the field of natural disaster emergency management in CNKI database from 2013 to 2022 by using weakly-supervised LDA,which reveals the hotness of the topics and the trend of evolution in each year.It is found that the existing research mainly focuses on the aspects of“Emergency Plan and Planning”and“Disaster early Warning System”,among which“Disaster Monitoring and Assessment”has become a significant hotspot.Over time,the attention to“Recovery and Reconstruction”gradually decreases,and“Disaster Risk Identification and Assessment”receives more attention.Research on natural disaster emergency management has gradually shifted from focusing on the application and effectiveness of emergency management methods,technologies and strategies to focusing on the full-cycle integrated management of disasters and long-term recovery.In the context of prevention beforehand,it is necessary to promote the full-cycle emergency management,deepen the core research and optimize the weak links.
作者
荆树伟
石丽英
刘金涛
Jing Shuwei;Shi Liying;Liu Jintao
出处
《中国应急管理科学》
2024年第6期34-51,共18页
Journal of China Emergency Management Science
基金
山西省哲学社会科学规划项目(201913120)
关键词
应急管理
主题演化
人工智能语言模型
自然灾害
弱监督LDA模型
Emergency Management
Thematic Evolution
Artificial Intelligence Language Modeling
Natural Disasters
Weakly Supervised LDA Models
