Urban Optimal Capital Structure Analysis based on Random Forest and Multi-objective Particle Swarm Optimization
[1]Li Yanyan,Yang Haotian,Zeng Yufan.Urban Optimal Capital Structure Analysis based on Random Forest and Multi-objective Particle Swarm Optimization[J].Journal of Zhengzhou University (Engineering Science),2019,40(04):14-.[doi:10.13705/j.issn.1671-6833.2019.04.028]
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Journal of Zhengzhou University (Engineering Science)[ISSN
1671-6833/CN
41-1339/T] Volume:
40卷
Number of periods:
2019 04
Page number:
14-
Column:
Public date:
2019-07-10
- Title:
- Urban Optimal Capital Structure Analysis based on Random Forest and Multi-objective Particle Swarm Optimization
- Keywords:
- random forest; Multi-objective particle swarm constrained optimization algorithm; City capital structure allocation; fit regression; Correlation
- CLC:
- -
- DOI:
- 10.13705/j.issn.1671-6833.2019.04.028
- Abstract:
- Urban capital structure was a complex?problem affected by multi-factors and multi-objective particle.This paper attempt ed to explore a scientific and appropriate d algorithm to construct the optimal capital structure model under the influence of multi-objective and multi-factors to analyze the situation of urban capital structure.First, the data in history could find the relationship among features of the data in history by using the regression characteristics of random forest. Then, the multi-objective particle swarm optimization algorithm was used to find values of the features that achieve the best results according to the existing relationship features. Then finding the most correlate data from the historical data based on the best eigenvalues of these effects. Therefore, the cities and the years with relatively better capital structure allocations are analyzed. We could play a good role in the reference and development of each city by continuously learning these superior structural configurations
- References:
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Last Update:
2019-07-29