Proceedings of the 2022 2nd International Conference on Management Science and Software Engineering (ICMSSE 2022)

Application of BP Neural Network in Tax Assessment of Real Estate Industry

Authors
Di Liu1, 2, Jiachun Li1, Zibo Zhao2, Jingyuan Yu3, Shi Zhang4, Changlin Ji1, *
1School of economics and management, Northeast Electric Power University, Jilin, 132012, China
2State Administration of Taxation Jilin Municipal Taxation Bureau No, Taxation Branch, Jilin, 132000, China
3State Administration of Taxation Jilin Municipal Taxation Bureau Inspection Bureau, Jilin, 132000, China
4School of electrical engineering, Northeast Electric Power University, Jilin, 132012, China
*Corresponding author. Email: 522707763@qq.com
Corresponding Author
Changlin Ji
Available Online 29 December 2022.
DOI
10.2991/978-94-6463-056-5_65How to use a DOI?
Keywords
Real estate industry; Pay taxes; Neural network; Evaluation index
Abstract

As one of the economic pillar industries in China, the real estate industry has great influence. The real estate industry involves many taxes, and the tax business is complicated, so it needs more attention. Tax assessment is an important part of tax work. Combined with the important economic significance of the real estate industry, the tax assessment of the real estate industry is particularly important. The tax assessment of real estate industry has the characteristics of long cycle, rich links, many taxes and so on, and it is very dependent on the subjective judgment of appraisers, so it takes a lot of energy. Therefore, the tax assessment of real estate industry based on artificial intelligence is a work worthy of in-depth study. This paper analyzes the common problems in tax assessment of real estate industry, including long development cycle leading to complicated tax-related business, imperfect contract management system, risk of paying less taxes, confusion of cost accounting objects, etc. This paper studies the commonly used evaluation indexes of tax assessment, including the related indexes of expense change rate and business profit change rate. Based on BP neural network, the tax assessment model of real estate industry is established, and the effectiveness of this method is verified by the actual data of five real estate enterprises in recent five years.

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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Volume Title
Proceedings of the 2022 2nd International Conference on Management Science and Software Engineering (ICMSSE 2022)
Series
Atlantis Highlights in Computer Sciences
Publication Date
29 December 2022
ISBN
978-94-6463-056-5
ISSN
2589-4900
DOI
10.2991/978-94-6463-056-5_65How to use a DOI?
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.

Cite this article

TY  - CONF
AU  - Di Liu
AU  - Jiachun Li
AU  - Zibo Zhao
AU  - Jingyuan Yu
AU  - Shi Zhang
AU  - Changlin Ji
PY  - 2022
DA  - 2022/12/29
TI  - Application of BP Neural Network in Tax Assessment of Real Estate Industry
BT  - Proceedings of the 2022 2nd International Conference on Management Science and Software Engineering (ICMSSE 2022)
PB  - Atlantis Press
SP  - 450
EP  - 454
SN  - 2589-4900
UR  - https://doi.org/10.2991/978-94-6463-056-5_65
DO  - 10.2991/978-94-6463-056-5_65
ID  - Liu2022
ER  -