Agricultural Products Supply Chain Risk Assessment Model Construction and Application in IOT Environment

Abstract

This paper constructs the operation model of agricultural products supply chain under an IoT (Internet of Things) environment, based on which the HHM (Hodrick-Prescott Filter) model is used to identify the risk. The ISM (Internal Supply Management) model was used to analyze risk factors. A risk index system was constructed, which was divided into three primary indexes and 18 secondary indexes. The backpropagation (BP) neural network approach was used to establish the risk assessment model. The sample data from 2017 to 2020 was employed as the test sample to test the network assessment model. There was a very small error in the risk level assessment and training results. The results showed that the risk level assessment model was highly operable and can have practical value for effective assessment of the risk level.