Constructing Financial Information Security Model Based on PCA and Optimized BP Neural Network
Chu Zhang · IETE Journal of Research · 2021
In recent years, with the rapid development of 5G technology, computer technology, communication technology, and the financial industry, people have paid more and more attention to financial information security issues. This article aims to use PCA technology and optimized BP neural network, and merge the two together to build a financial information security model and conduct in-depth research. This paper proposes the PCA technology, the principal component analysis technology, which uses the concept of dimensionality reduction to convert multiple indexes into partially integrated indexes. It is a data set simplification technology and the reverse propagation algorithm training according to a certain error. The BP neural network with many levels and multiple feedbacks carried out a financial information security model simulation experiment, and finally obtained experimental data to support the model. The experimental results of this article show that in 2020, my country has become the country with the highest network coverage in the world, reaching 64.3%, and the number of denizens has reached 632 million. In this experiment, there are a total of 13,896 pieces of useful data, including 4 types. Therefore, current research attaches great importance to the field of financial information security.