Research Trend Analysis of Artificial Intelligence Rainfall Prediction Algorithms Based on Knowledge Networks

<jats:title>Abstract</jats:title>
<jats:p>This research uses CiteSpace software as a tool to sort out the research results of artificial intelligence-based rainfall prediction models and algorithms in the China Knowledge Network Database (CNKI) and the “Web of Science” database, summarize relevant research hotspots and topics, and identify the latest research Trends, provide a reference for further advancement of rainfall prediction models and algorithms. Through knowledge network analysis, the following conclusions are drawn: (1) The literature based on rainfall prediction models and algorithms has shown an increasing trend over time. (2) It is scientific research institutions and colleges and universities of various countries that publish a large number of relevant documents. (3) The current research trend is deep learning and meteorological satellites. Neural networks tend to study a variety of data assimilation and hybrid models. (4) Global artificial intelligence-based rainfall prediction models and algorithms research results show that more emphasis is placed on deep learning algorithms Application trends.</jats:p>