Peng Yixiao
School of Economics, Zhejiang University of Technology, Hangzhou 310023, Zhejiang, China.
J Environ Public Health. 2022 Jul 6;2022:3393532. doi: 10.1155/2022/3393532. eCollection 2022.
Urbanization has accelerated China's economic growth, but it has also brought many sustainability issues. This paper selected a random forest model to study the impact of local government-led urbanization on urban sustainable development. Urbanization affected urban sustainable development through government revenue expansion, land resources mismatch, and industrial structure adjustment. The results showed that the adjustment of industrial structure has the greatest impact on urban sustainable development, and the importance of the average output of industrial enterprises confirms it. Government revenue expansion and land resources mismatch are more important to the sustainable development of representative urban agglomerations. The goodness of fit of the random forest model is better than the multiple linear regression (MLR) model and the extreme gradient boosting (XGBoost) model. The generalization ability of the model is improved with the optimization of variables. The main contribution of this paper is that we have established a complete information dynamic game model on government revenue expansion, land resource mismatch, industrial structure adjustment, and urban sustainable development. And the random forest model is used to study the relationship between the above variables.
城市化加速了中国的经济增长，但也带来了许多可持续发展问题。本文选取随机森林模型来研究地方政府主导的城市化对城市可持续发展的影响。城市化通过政府财政收入扩张、土地资源错配和产业结构调整影响城市可持续发展。结果表明，产业结构调整对城市可持续发展的影响最大，工业企业平均产出的重要性证实了这一点。政府财政收入扩张和土地资源错配对于代表性城市群的可持续发展更为重要。随机森林模型的拟合优度优于多元线性回归（MLR）模型和极端梯度提升（XGBoost）模型。随着变量的优化，模型的泛化能力得到提高。本文的主要贡献在于，我们建立了一个关于政府财政收入扩张、土地资源错配、产业结构调整和城市可持续发展的完整信息动态博弈模型。并使用随机森林模型来研究上述变量之间的关系。
