Abstract：The evolution of urban innovation space development varies greatly, and it is of great practical significance to pay attention to its causes and the key influencing factors of its evolution. Taking Wuhan main city as an example, the machine learning algorithm, and Random Forest Modeling Algorithm is used to analyze the influencing factors on the evolution of Wuhan’s innovation space. The results show that the Random Forest Modeling algorithm fits the dataset well, can effectively capture the complex nonlinear characteristics of the influencing factors and the evolution of innovation space, and reveals that the important factors affecting the evolution of the innovation space are population density, distance from commercial centers, subway station density and road network density. Finally, we make suggestions for the future development of urban innovation space based on this evidence.
陈从心 张萍 韩叙. 基于随机森林模型算法的城市创新空间演变影响要素研究
——以武汉市主城区为例[J]. 新建筑, 2024, 42(1): 114-117.
CHEN Congxin ZHANG Ping HAN Xu. Research on the Influential Elements of Urban Innovation Space Evolution Based on Random Forest Model Algorithm: Taking Wuhan Main City as an Example. New Architecture, 2024, 42(1): 114-117.
版权所有 © 2017 新建筑杂志社