Study on the US Presidential Election Based on Neural Network

Abstract

The world's most watched U.S. election is in a state of anxiety, with Republican candidate Donald John Trump and Democratic candidate Joe Biden will compete for the presidency this month. The two candidates will show different political positions and administrative options in different areas of development and domestic and foreign policy. The election of different candidates will have a great impact on the United States economy and the global economy, and will have a great impact on the trend of international relations. In response to question one, we need to analyze the possible impact of election of different candidates on the United States economy. We first quantitatively analyze the policy data of the two candidates obtained in the network in different fields. By merging the quantitative models of different fields, the AHP is used to calculate the weights of different fields, and the comparison between two candidates in each field and the impact on the American economy. According to the large data set collected, we do cluster analysis, and analyze and predict the impact of different fields by BP neural network model. For the second question, in order to analyze the impact of different candidate is elected to the Chinese economy, according to the problem a model for analysis, in order to improve the accuracy of the model, this part adds more considerations variables, at the same time, higher precision, based on genetic algorithm neural network model, after finishing the data concentration, 80% of the data used in the model, variables to determine index weight and threshold, the remaining 20% of the data by residual error calculation is used to model accuracy test. In view of question three, through the analysis of question one and question two and the actual situation, we can get the final winning candidate. And through the analysis of its economic and policy means to give China's economic countermeasures and policies in related fields. By referring to a large amount of data, this paper finally obtains the influence of different candidates on the united states, china and the global economy and politics through data visualization analysis of different candidates' policy claims in different fields. In order to further improve the model accuracy and computational efficiency, this paper also proposes to use Levenberg-Marquardt-based algorithm to solve the problem.