Analysis and Forecast of Shanghai Financial Revenue Based on Data Mining

DOI

10.2991/icmcs-18.2018.31How to use a DOI?

Keywords

Shanghai fiscal revenue; Adaptive-Lasso; Grey prediction; Neural network

Abstract

After 1994, the fiscal management system that China began to implement was a tax-sharing system. Local fiscal revenue was an important fund for local governments to carry out macroeconomic regulation and control. Based on the data of Shanghai's fiscal revenue and its influencing factors from 1994 to 2016, based on the Adaptive-Lasso variable selection method, the combination of grey prediction and neural network is used to fit and predict Shanghai's fiscal revenue. Providing data support for the Shanghai Municipal Government, and also providing reference for other cities with faster economic development.

Copyright

© 2018, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Wei Deng
PY  - 2018/10
DA  - 2018/10
TI  - Analysis and Forecast of Shanghai Financial Revenue Based on Data Mining
BT  - Proceedings of the 8th International Conference on Management and Computer Science (ICMCS 2018)
PB  - Atlantis Press
SP  - 157
EP  - 161
SN  - 2352-538X
UR  - https://doi.org/10.2991/icmcs-18.2018.31
DO  - 10.2991/icmcs-18.2018.31
ID  - Deng2018/10
ER  -