Application of Bayesian Analysis Based on Neural Network and Deep Learning in Data Visualization
Year: 2024
Type: article
Abstract: This study aims to explore the application of Bayesian analysis based on neural networks and deep learning in data visualization. The research background is that with the increasing amount and complexity of data, traditional data analysis methods have been unable to meet the needs. Research methods include building neural networks and deep learning models, optimizing and improving them through Bayesian analysis, and applying them to the visualization of large-scale data sets. The results show that the neural network combined with Bayesian analysis and deep learning method can effectively improve the accuracy and efficiency of data visualization, and enhance the intuitiveness and depth of data interpretation. The significance of the research is that it provides a new solution for data visualization in the big data environment and helps to further promote the development and application of data science.
Authors: Jiying Yang, Qi Long, Xiaoyun Zhu, Yuan Yang
Institution: Yunnan Open University
Language: English
Subfield: Computer Vision and Pattern Recognition
Field: Computer Science
Domain: Physical Sciences
Open Access status: diamond
OpenAlex ID: W4401623398