Energy-saving feature extraction method for urban buildings with near-zero energy-consuming based on SVR Online publication date: Thu, 12-Nov-2020
by Xiaoliang Li; Jinfeng Lu
International Journal of Global Energy Issues (IJGEI), Vol. 42, No. 5/6, 2020
Abstract: In order to solve the problem of poor fitting performance of traditional energy saving feature extraction method in urban buildings with near zero energy consumption, an energy saving feature extraction method based on SVR is proposed. The data are recovered and processed by means of mean value substitution method, and the correlation order of data parameters is realised through grey correlation analysis. Based on the feature weighting theory, the energy saving data of near zero energy saving buildings are cluster analysed. The main component analysis method is used to deal with feature extraction data, reduce the size of feature extraction data, and use SVR to achieve the extraction of energy saving characteristics of nearly zero energy consumption buildings in cities. The experimental results show that the method is always higher than other methods, with a maximum of 88%. The results show that the method is effective in feature extraction.
Existing subscribers:
Go to Inderscience Online Journals to access the Full Text of this article.
If you are not a subscriber and you just want to read the full contents of this article, buy online access here.Complimentary Subscribers, Editors or Members of the Editorial Board of the International Journal of Global Energy Issues (IJGEI):
Login with your Inderscience username and password:
Want to subscribe?
A subscription gives you complete access to all articles in the current issue, as well as to all articles in the previous three years (where applicable). See our Orders page to subscribe.
If you still need assistance, please email subs@inderscience.com
Our Blog 
Follow us on Twitter 
Visit us on Facebook