Research on urban modern architectural art based on artificial intelligence and GIS image recognition system

被引:10
|
作者
Huang W. [1 ]
Ren J. [2 ]
Yang T. [1 ]
Huang Y. [1 ]
机构
[1] School of Civil Engineering and Architecture, Shaanxi University of Technology, Hanzhong
[2] Collaborative Innovation Center of Biological Resources in Qinba Mountains, Shaanxi University of Technology, No.1 Dongyihuan Road, Hanzhong, 723001, Shaanxi
关键词
Artificial intelligence; GIS; Image recognition; Urban architecture;
D O I
10.1007/s12517-021-07222-z
中图分类号
学科分类号
摘要
At present, the Chinese construction industry has begun to apply artificial intelligence technology to the research of the construction industry, and it has attracted the attention of many researchers. At present, the main application method is in the construction of the internal system of the intelligent building, use the neural network system, the mold control system, the expert system, and the intelligent decision-making system to achieve the goal of the intelligent building service. This article will analyze the overall situation of artificial intelligence applications in intelligent construction at this stage, based on artificial intelligence technology, and study in detail the application of artificial intelligence systems in various aspects of intelligent construction. Re-excavate the connotation of the urban texture with the methods of quantification and data analysis. Take the texture data of multiple cities as an example, and use methods such as image dimensionality reduction, k-means clustering, convolutional neural network classification, and machine learning to build urban images. The identification and evaluation system finally concludes that in the existing evaluation system, the total economic score, the total soft economic score, the environmental score, and the sanitation score have the greatest correlation with the recognition results of urban texture. Among them is the environmental score. The correlation of health scores is in line with the common cognition of urban research scholars, and the calculation results of total economic scores and total soft economic scores indicate that urban architectural planning and its layout are hidden from the economic situation of the city, and also prove artificial intelligence based on image recognition is necessary to mine city information and evaluate it. © 2021, Saudi Society for Geosciences.
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