Evaluation method and device for flood influence field by different technologies, and medium

By combining social website comment data and rainfall data, building a corpus of technologies and fields and performing causal path analysis, the problem that existing technologies are difficult to evaluate the impact of different technologies on floods is solved, and the effect of real-time and accurate assessment of the impact of flood disasters and optimizing the post-disaster recovery strategy is achieved.

CN119721814APending Publication Date: 2025-03-28INST OF URBAN ENVIRONMENT CHINESE ACAD OF SCI
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Patent Information

Application Number
CN202411764421.1
Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
Filing Date
2024-12-03
Publication Date
2025-03-28

AI Technical Summary

Technical Problem

It is difficult for existing technologies to effectively evaluate the areas and extent of the impact of different technologies on floods, especially in post-disaster recovery and assessment in late floods.

Method used

By collecting social website comment data and rainfall data, text preprocessing and keyword matching, building corpus of technologies and fields, generating time series of technical indexes and domain indexes, and causal path analysis is performed through LDA thesis modeling and SEM structural equation modeling to evaluate the importance and impact areas of different technologies on flooding.

Benefits of technology

Real-time and accurate assessment of the impact of different technologies on various fields in flood disasters has been achieved, helping to optimize post-disaster recovery strategies and improve urban resilience to floods.

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Abstract

The invention relates to a method and equipment for evaluating the field of influence of different technologies on flood and a medium, and the method comprises the steps: collecting social network site comment data and rainfall data, and screening out the comment data related to the flood from the social network site comment data and the rainfall data; constructing corpora corresponding to each technology and each field based on the comment data; based on the occurrence times of the corresponding keywords at different time points in the corpus, constructing a time sequence of the occurrence times of the keywords corresponding to the technologies and the fields along with time change; high-frequency keywords corresponding to the technologies are obtained through LDA topic modeling; further determining the importance degree of each technology to each field and other technologies; constructing a plurality of causal paths in combination with the influence of rainfall on each field; and converting the causal path into a plurality of structural equation models, and screening an optimal causal path model corresponding to each field. According to the method, text mining and a causal model based on statistics are combined, so that the influence of different technologies on the flood disaster on the field is evaluated.
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