Exploring the Spatial Impact of Multisource Data on Urban Vitality: A Causal Machine Learning Method
| العنوان: | Exploring the Spatial Impact of Multisource Data on Urban Vitality: A Causal Machine Learning Method |
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| المؤلفون: | Zhixuan Xiao, Chengyi Li, Shihua Pan, Gaoda Wei, Mengmeng Tian, Runjiu Hu |
| المصدر: | Wireless Communications and Mobile Computing. 2022:1-24 |
| بيانات النشر: | Hindawi Limited, 2022. |
| سنة النشر: | 2022 |
| مصطلحات موضوعية: | Article Subject, Computer Networks and Communications, Electrical and Electronic Engineering, Information Systems |
| الوصف: | Identifying urban vitality is the key to optimizing the urban structure. Previous studies on urban multisource data and urban vitality often assume that they follow a predefined (linear or nonlinear in terms of parameters) relationship, and few studies have explored the causality of urban multisource data on urban vitality. The existing machine learning methods often pay attention to the correlation in the data and ignore the causality. With the continuous emergence of new needs, its disadvantages gradually begin to appear and face a series of urgent problems in interpretability, robustness, and fairness. In this paper, we use a combination of causal inference and machine learning to deeply explore and analyze the causal effects of multisource data on the 16 administrative districts of Shanghai, taking Shanghai as an example. The analysis results show that each data indicator has different degrees of influence on the urban vitality of the 16 administrative districts of Shanghai, resulting in different heterogeneous effects, and through the analysis result, each administrative district can better optimize urban resources and improve urban vitality according to its situation. This discovery guides urban planning and has enlightenment significance for cities seeking construction facility investment and facility construction-oriented development. |
| وصف الملف: | text/xhtml |
| تدمد: | 1530-8677 1530-8669 |
| URL الوصول: | https://explore.openaire.eu/search/publication?articleId=doi_dedup___::baccd2c7f2cfa771eb38f36933cfe063 https://doi.org/10.1155/2022/5263376 |
| حقوق: | OPEN |
| رقم الأكسشن: | edsair.doi.dedup.....baccd2c7f2cfa771eb38f36933cfe063 |
| قاعدة البيانات: | OpenAIRE |
| تدمد: | 15308677 15308669 |
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