| id |
ecaade2017_019 |
| authors |
Liu, Yuezhong, Stouffs, Rudi and Tablada, Abel |
| year |
2017 |
| title |
Rethinking the Urban Design Process from a Data Perspective |
| doi |
https://doi.org/10.52842/conf.ecaade.2017.1.449
|
| source |
Fioravanti, A, Cursi, S, Elahmar, S, Gargaro, S, Loffreda, G, Novembri, G, Trento, A (eds.), ShoCK! - Sharing Computational Knowledge! - Proceedings of the 35th eCAADe Conference - Volume 1, Sapienza University of Rome, Rome, Italy, 20-22 September 2017, pp. 449-460 |
| summary |
Urban design always requires the processing of large amounts of data from multi-disciplinary sources during the decision-making stages. However, unfamiliar multi-disciplinary data sets can only lead to confusion and uncertainty. This research proposes a data-driven approach for supporting the urban design process. A hybrid data mining method is used to cluster, classify and rank solution-instances according to geometrical properties and energy performance. An urban design case study is used to demonstrate the proposed method with respect to two performance issues: solar heat gains and natural ventilation. The result shows that the method addressing both familiar and unfamiliar data can effectively guide the designer during the design process. |
| keywords |
energy performance; S3VM; decision tree; familiar and unfamiliar |
| series |
eCAADe |
| email |
liuyuezhong@u.nus.edu |
| full text |
 file.pdf (30,386,146 bytes) |
| references |
Content-type: text/plain
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| last changed |
2022/06/07 07:59 |
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