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.

摘要

为探究贸易不确定性对全国粮食供应的影响，本文基于BP神经网络算法，结合粮食供应特点和贸易数据，构建智能分析模型。此外，本文以历史数据为基础数据，研究粮食供应的贸易不确定性和相关特征，结合实际需求构建BP神经网络模型结构。构建模型后,分析模型的作用,结合比较分析法对数据进行分类,研究贸易不确定性对全国粮食供给的影响机制。另外，本文结合实际数据分析了本文算法模型的性能，分析结果与历史数据一致。最后,本文基于模型分析结果对国家粮食供应成本控制进行了分析,并提出了若干对策。