Countermeasures for Improving Rural Living Environments under the Background of a Rural Revitalization Strategy Based on Computer Virtualization Technology

Bowen Sun, Husheng Pan and Shanshan Shao ()
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Bowen Sun: Academy of Arts & Design, Tsinghua University, Beijing 100084, China
Husheng Pan: Academy of Arts & Design, Tsinghua University, Beijing 100084, China
Shanshan Shao: School of Chinese Language and Literature, Shaanxi Normal University, Xi’an 710119, China

Sustainability, 2023, vol. 15, issue 8, 1-14

Abstract: The all around construction and development of rural areas not only promotes the economic promotion of rural areas and the optimization and adjustment of various industrial structures, but also leads to the deterioration of rural living environments. There is a close relationship between the planning and design of residential buildings and the living environment, which can integrate human life and architecture into a whole. Virtualization technology is a new technology developed in recent years, which integrates computer graphics, multimedia, digital image processing, and other technologies. In this paper, a virtual building model of a rural residential environment based on a convolutional neural network (CNN) is constructed, and the virtual reconstruction of the residential environment is realized by extracting the bottom features of images. The experimental results show that, compared with the support vector machine (SVM) algorithm, the accuracy of the proposed human settlements modeling method is improved by 27.85%. This model can effectively solve the problem of unclear and not stereo images, and at the same time keep the clarity of the virtual reconstruction images of buildings, which can provide theoretical support for the improvement of the rural living environment under the background of a rural revitalization strategy.

Keywords: human settlement environment; rural revitalization; virtualization technology; convolutional neural network (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2023
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