Artificial intelligence rainstorm prediction model construction method based on multi-source heterogeneous data fusion

Abstract

The invention discloses an artificial intelligence rainstorm prediction model construction method based on multi-source heterogeneous data fusion, and relates to the technical field of rainstorm prediction, and the method comprises the steps: collecting multi-source meteorological data of a to-be-predicted region, the meteorological data comprising satellite remote sensing data, weather radar data, ground meteorological station data and numerical prediction mode data; dividing the to-be-predicted region into different dominant type regions based on a preset dominant factor discrimination rule, and constructing a virtual cloud cluster entity based on the dominant type regions; a motion model of a virtual cloud cluster entity is established, a life development track of the virtual cloud cluster entity is generated, and then a cloud cluster motion map reflecting dynamic evolution of the virtual cloud cluster entity is constructed; the system analyzes and generates an intervention instruction based on the cloud cluster motion map, projects the intervention instruction into the cloud cluster motion map, and finally outputs a rainstorm prediction report including deterministic early warning and potential risk assessment; according to the invention, a virtual cloud cluster entity system with dynamic perception and active intervention capabilities is constructed, and accurate prediction of the rainstorm formation process is realized.

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