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Issue title: Special section: Artificial Intelligence driven Big Data Analytics for COVID-19
Guest editors: Xiaolong Li
Article type: Research Article
Affiliations: College of Fine Arts, Hubei Normal University, Huangshi, Hubei, China
Correspondence: [*] Corresponding author. Guo, Chen, College of Fine Arts, Hubei Normal University, Huangshi 435002, Hubei, China. E-mail: 38837440@qq.com.
Abstract: In rural construction, affected by covid-19, it leads to the collection and demand survey of basic information data of relevant interest groups. The specific situation of the transformation of ancient villages is also gradually increasing. However, due to the complexity of rural space, the dispersion of settlement space and the diversity of information demand of rural planning work, the data coverage is large, information acquisition is difficult, the use effect of data collection is not ideal, and there is no planning feedback mechanism. However, during the epidemic period, the staff could not carry out a series of reconstruction of ancient villages. At present, the data of village planning and construction and architectural design are complex, the needs of relevant interest groups are diversified, and regional planning is difficult. In this paper, the big data function is applied to the reconstruction of ancient villages in the epidemic period of covid-19.
Keywords: Reconstruction of ancient villages, big data, regional co-ordination, rural architecture design, COVID-19
DOI: 10.3233/JIFS-189278
Journal: Journal of Intelligent & Fuzzy Systems, vol. 39, no. 6, pp. 8813-8821, 2020
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