Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
6775866 | Sustainable Cities and Society | 2016 | 6 Pages |
Abstract
The rapidly growing and gigantic body of stored data in the building field, coupled with the need for data analysis, has generated an urgent need for powerful tools that can extract hidden but useful knowledge of building performance improvement from large data sets. As an emerging subfield of computer science, data mining technologies suit this need well and have been proposed for relevant knowledge discovery in the past several years. Aimed to highlight recent advances, this paper provides an overview of the studies undertaking the two main data mining tasks (i.e. predictive tasks and descriptive tasks) in the building field. Based on the overview, major challenges and future research trends are also discussed.
Related Topics
Physical Sciences and Engineering
Energy
Renewable Energy, Sustainability and the Environment
Authors
Zhun (Jerry) Yu, Fariborz Haghighat, Benjamin C.M. Fung,