Application of Bayesian Analysis Based on Neural Network and Deep Learning in Data Visualization

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.

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Publication Details

Journal
Journal of Electronic Research and Application
Published
2024-08-12
DOI
https://doi.org/10.26689/jera.v8i4.7924
Citations
2
Primary Topic
Advanced Decision-Making Techniques
Type
article
Field-Weighted Citation Impact
1.56
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article

Application of Bayesian Analysis Based on Neural Network and Deep Learning in Data Visualization

Yang Ji-ying, Xiaoyun Zhu, Yuan Yang, Qi Long
2 citations
Journal of Electronic Research and Application
Advanced Decision-Making Techniques
1.56
article

Application of Bayesian Analysis Based on Neural Network and Deep Learning in Data Visualization

Yang Ji-ying, Xiaoyun Zhu, Yuan Yang, Qi Long
article en
2 citations

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.

Journal of Electronic Research and ApplicationVol. 8(4)
Yunnan Open University (CN)
Industry, innovation and infrastructure
Openalex Percentile: Top 13%
Advanced Decision-Making Techniques
1.56
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Application of Bayesian Analysis Based on Neural Network and Deep Learning in Data Visualization — Yang Ji-ying, Xiaoyun Zhu, et al. · Journal of Electronic Research and Application (2024) | TGRS Research Map | TGRS