Progress and Hotspot Analysis of Machine Learning in Domestic Urban Flood Disaster Research
As a new technical method,machine learning has been increasingly applied in the study of urban flood disaster in recent years.The bibliometric visualization tool CiteSpace is used to sort out and analyze the research on urban flood disaster based on machine learning in China from 1986 to 2024,which reveals the overall development trend,research hotspots and future trends in the research field.The main conclusions are that(1)The number of research achievements of machine learning in domestic urban flood disasters has experienced four stages:steady,warming,fluctuating and rapidly rising.(2)Research authors and research institutions present a certain degree of clustering.Only about half of the published journals belong to the core journals,and the proportion of CSCD and CSSCI journals is not high.(3)The content of machine learning in urban flood disaster research is diversified.In the past,the flood forecasting research has gradually shifted to flood disaster risk assessment.
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