Public Budget Revenue Model Based on SVR and Neural Network-A Case Study of Shanxi Province

DOI

10.2991/978-94-6463-200-2_91How to use a DOI?

Keywords

public budget revenue; lasso; SVR; BP; GM (1,1)

Abstract

This paper analyzes a variety of factors that affect public budget revenue. The data set is the Shanxi Provincial Statistical Yearbook collected from 1999 to 2021 years. This study uses the lasso regression method to select multiple factors affecting public budget revenue. The key influencing factors were retained. Then the GM (1,1) model was used to predict the data of each influencing factor in 2022 and 2023. Finally, SVR and neural network were used to forecast the public budget revenue in 2022 and 2023 and the advantages and disadvantages of the two models were compared. The results show that the general economic pattern of Shanxi province will be positive in the future. The public budget revenue of Shanxi Province will further increase.

Copyright

© 2023 The Author(s)

Open Access

Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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TY  - CONF
AU  - Li Fang
AU  - Yuan Liu
AU  - Qing Zhao
AU  - Jing Yang
AU  - Luoyifan Zhong
PY  - 2023
DA  - 2023/07/26
TI  - Public Budget Revenue Model Based on SVR and Neural Network-A Case Study of Shanxi Province
BT  - Proceedings of the 2023 3rd International Conference on Public Management and Intelligent Society (PMIS 2023)
PB  - Atlantis Press
SP  - 872
EP  - 883
SN  - 2589-4919
UR  - https://doi.org/10.2991/978-94-6463-200-2_91
DO  - 10.2991/978-94-6463-200-2_91
ID  - Fang2023
ER  -