Research on the impact of trade uncertainty on national grain supply and risk cost control

Abstract

In order to explore the impact of trade uncertainty on the national grain supply, based on the BP neural network algorithm, this paper combines the characteristics of grain supply and trade data to construct an intelligent analysis model. Moreover, this paper uses historical data as the basic data to study the trade uncertainty and the relevant characteristics of grain supply, and combine the actual demand to construct the structure of the BP neural network model. After constructing the model, this paper analyzes the function of the model, combines the comparative analysis method to classify the data and studies the influence mechanism of trade uncertainty on the national grain supply. In addition, this paper combines the actual data to analyze the performance of the algorithm model of this paper, and the analysis results are consistent with historical data. Finally, this paper analyzes the cost control of national grain supply based on the results of the model analysis, and proposes several countermeasures.

Keywords

• uncertainty in trade
• national grain
• risk cost
• agricultural finance
• total supply and demand
• bp neural network
• weight adjustment principle