A Graph Neural Network-Based Electric-Field Prediction Model for Exposure Assessments

Sen Liu,Teruo Onishi,Masao Taki,Soichi Watanabe

2023 IEEE International Symposium on Antennas and Propagation and USNC-URSI Radio Science Meeting (USNC-URSI)（2023）

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摘要

Grasping the electric-field (E-field) distribution is challenging yet important for monitoring the electromagnetic field (EMF) exposure level. In this paper, a graph neural network (GNN)-based prediction model is proposed to estimate the E-field distribution in a complex indoor environment. The model provides a good accuracy and has an appealing feature of being quite efficient.

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关键词

complex indoor environment,E-field distribution,electric-field distribution,electromagnetic field,EMF,exposure assessments,GNN,graph neural network-based electric-field prediction model,graph neural network-based prediction model

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