| Issue |
E3S Web Conf.
Volume 214, 2020
2020 International Conference on Energy Big Data and Low-carbon Development Management (EBLDM 2020)
|
|
|---|---|---|
| Article Number | 02011 | |
| Number of page(s) | 10 | |
| Section | Machine Learning and Energy Industry Structure Forecast Analysis | |
| DOI | https://doi.org/10.1051/e3sconf/202021402011 | |
| Published online | 07 December 2020 | |
Research on Discrete Dynamic Forecasting Model of Government Human Resources
Henan Institute of Science and Technology, Xinxiang City, Henan Province, China 453003
Corresponding Author Mail: Qin Li, LL19890703@126.com
For the evolution of complex system, especially the unbalanced complex system, dynamic is its universal attribute. In this paper, by introducing the discrete dynamic system model in complex system research, a method of establishing the discrete dynamic system model of government human resources system is proposed from the vertical level. In this study, human resources were forecasted by the method of manpower/population ratio, linear regression and grey system, and the total number of health human resources in A city from 2018 to 2022 was forecasted by weighted average combination method. The results show that we should make great efforts to innovate the training mode of health personnel, improve the enthusiasm of staff, and reasonably control the expansion of hospitals.
© The Authors, published by EDP Sciences, 2020
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