A New Employment Forecast Model and Empirical Study Based on BP Neural Network

DOI

10.2991/icmmct-17.2017.269How to use a DOI?

Keywords

BFGS; BP neural networks; Forecast; Countermeasures

Abstract

Since 2006, the labor market in China continued to increase a lot. Based on the analysis of main factors which affecting the labor market, this paper uses BP neural networks based on BFGS to forecast the labor market in China. First of all, dealing with the initial data, try the best to meet the requirements of BP neural network. And then, it is required to accumulate an appropriate BP neural network model, by using the actual data to verify this model. After that, comparing it with traditional statistical models, proving that the prediction model of BP neural network based on BFGS has a higher precision and practicability.

Copyright

© 2017, 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  - Rui Huang
AU  - Xi Chang
AU  - Danni Zhao
PY  - 2017/04
DA  - 2017/04
TI  - A New Employment Forecast Model and Empirical Study Based on BP Neural Network
BT  - Proceedings of the 2017 5th International Conference on Machinery, Materials and Computing Technology (ICMMCT 2017)
PB  - Atlantis Press
SP  - 1410
EP  - 1420
SN  - 2352-5401
UR  - https://doi.org/10.2991/icmmct-17.2017.269
DO  - 10.2991/icmmct-17.2017.269
ID  - Huang2017/04
ER  -