Affiliations: [a] School of Urban Design, Wuhan University, Hubei Province, China
| [b] School of Architecture, Chang’an University, Xi’an, China
Correspondence:
[*]
Corresponding author. Shidan Cheng, School of Urban Design, Wuhan University, Wuhan City, Hubei Province, China. E-mail: boliming20190808@163.com.
Abstract: Green buildings have many advantages that traditional buildings do not possess, but there are still problems such as insufficient promotion and application. One of the important reasons is the lack of pertinent evaluation of green buildings. The current assessment of the economic benefits of green building design is still at a qualitative stage, and there is a lack of quantitative assessment methods and models. Based on this, this study establishes a green building design evaluation index system including cost and economic benefits. In the cost estimation, a nonlinear evaluation model based on data mining is designed to ensure a better estimation accuracy and credibility. In the evaluation of economic benefits, an incremental benefit evaluation model based on fuzzy mathematics is designed to evaluate its comprehensive economic benefits in a quantitative way. The results of data simulation show that the least squares support vector machine has achieved a good balance between the estimation time and accuracy. The comprehensive evaluation model proposed in this paper has strong operability and good evaluation effect, which is of great significance to promote the development of green building design.
Keywords: Green building design, data mining, fuzzy mathematics, comprehensive
evaluation
