公开(公告)号：US20240054339A1

公开(公告)日：2024-02-15

申请号：US17990617

申请日：2022-11-18

Applicant: ZHEJIANG LAB

Inventor： Hongyang CHEN ,  Bingyang HU ,  Qingguo QI ,  Zhao LI

IPC: G06N3/08

CPC classification number: G06N3/08

Abstract: Disclosed are a method and system for predicting spatio-temporal perception information based on a graph neural network. The method includes the following steps: step S1: constructing a perception data monitoring network, and acquiring original perception data through data acquisition nodes in the perception data monitoring network; step S2: pre-processing the original perception data and converting the same into spatio-temporal graph perception data; step S3: constructing a graph neural network model, and training parameters of the graph neural network model by using the spatio-temporal graph perception data; and step S4: inputting given spatio-temporal graph perception data to the trained graph neural network model and outputting a predicted value, and sending early warning information when the predicted value exceeds a preset threshold.