Proceedings of the 2026 2nd International Conference on Data Mining and Project Management (DMPM 2026)

Construction of a Risk Assessment System for Green Transformation of Urban Buildings Based on K-means Clustering

Authors
Lushan Shi1, *
1School of Architecture and Civil Engineering, Xiamen Institute of Technology, Xiamen, Fujian, 361021, China
*Corresponding author. Email: sls76333@126.com
Corresponding Author
Lushan Shi
Available Online 28 May 2026.
DOI
10.2991/978-94-6239-689-0_4How to use a DOI?
Keywords
Urban Architecture; Green Transformation; Risk Assessment; k-means Clustering Algorithm
Abstract

In the context of the new era, people’s yearning for a better life requires the construction field to provide a more comfortable and healthy living environment in a greener, environmentally friendly and efficient way. The green transformation of existing buildings often involves more stakeholders, and the risk factors associated with them are also more difficult to manage due to complex interest relationships, which greatly inhibits the enthusiasm of project sponsors to invest and residents to transform. In this paper, the k-means clustering algorithm is used to conduct risk network centrality analysis, risk network connection hub analysis, and risk factor influence analysis to study the role and influence of risk factors related to various stakeholders in the structure and dissemination of risk networks. It is found that there is a lack of effective daily operation feedback mechanism, uneven ability of management personnel, poor professional ability, lack of relevant professional and technical personnel, construction funds cannot be in place in time, and engineering changes. These risks occur most frequently in the green transformation of urban buildings. Risks with the characteristics of connecting hubs have a greater influence on the spread of risk networks and the closeness of risk relationships than risks with the characteristics of risk sources.

Copyright
© 2026 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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Volume Title
Proceedings of the 2026 2nd International Conference on Data Mining and Project Management (DMPM 2026)
Series
Advances in Economics, Business and Management Research
Publication Date
28 May 2026
ISBN
978-94-6239-689-0
ISSN
2352-5428
DOI
10.2991/978-94-6239-689-0_4How to use a DOI?
Copyright
© 2026 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Cite this article

TY  - CONF
AU  - Lushan Shi
PY  - 2026
DA  - 2026/05/28
TI  - Construction of a Risk Assessment System for Green Transformation of Urban Buildings Based on K-means Clustering
BT  - Proceedings of the 2026 2nd International Conference on Data Mining and Project Management (DMPM 2026)
PB  - Atlantis Press
SP  - 27
EP  - 35
SN  - 2352-5428
UR  - https://doi.org/10.2991/978-94-6239-689-0_4
DO  - 10.2991/978-94-6239-689-0_4
ID  - Shi2026
ER  -