TY - JOUR
T1 - The quantitative investigation on people's pre-evacuation behavior under fire
AU - Liu, M.
AU - Lo, S. M.
PY - 2011/8
Y1 - 2011/8
N2 - With the growth in urbanization process and activities in Hong Kong and many large cities in China, a great number of super high-rise buildings have been constructed in these years. The occurrences of many large fire tragedies, especially the US 9/11 terrorist attack, made people aware that super high-rise buildings may cause serious fatalities, and extremely they could collapse in a huge uncontrolled fire. Compared with people's evacuation behavior, little interests have been drawn to pre-movement behavior. In Hong Kong and some major cities in China, over 90% of people are living in multi-storey multi-compartment buildings. Their awareness and responses to fire incidents happening in the other parts of the same building have substantial influence on the whole evacuation process. Studies on pre-evacuation human behavior have been performed for many years, but the vast majority of the studies were qualitative-oriented. Accordingly, an attempt was made in this article to quantitatively investigate people's pre-evacuation behavior by using the Support Vector Machine (SVM) approach, which was trained by Hong Kong's post-fire field survey data. © 2010 Elsevier B.V. All rights reserved.
AB - With the growth in urbanization process and activities in Hong Kong and many large cities in China, a great number of super high-rise buildings have been constructed in these years. The occurrences of many large fire tragedies, especially the US 9/11 terrorist attack, made people aware that super high-rise buildings may cause serious fatalities, and extremely they could collapse in a huge uncontrolled fire. Compared with people's evacuation behavior, little interests have been drawn to pre-movement behavior. In Hong Kong and some major cities in China, over 90% of people are living in multi-storey multi-compartment buildings. Their awareness and responses to fire incidents happening in the other parts of the same building have substantial influence on the whole evacuation process. Studies on pre-evacuation human behavior have been performed for many years, but the vast majority of the studies were qualitative-oriented. Accordingly, an attempt was made in this article to quantitatively investigate people's pre-evacuation behavior by using the Support Vector Machine (SVM) approach, which was trained by Hong Kong's post-fire field survey data. © 2010 Elsevier B.V. All rights reserved.
KW - Fire evacuation
KW - Pre-evacuation human behavior
KW - Predictive tool
UR - http://www.scopus.com/inward/record.url?scp=79957506909&partnerID=8YFLogxK
UR - https://www.scopus.com/record/pubmetrics.uri?eid=2-s2.0-79957506909&origin=recordpage
U2 - 10.1016/j.autcon.2010.12.004
DO - 10.1016/j.autcon.2010.12.004
M3 - RGC 21 - Publication in refereed journal
SN - 0926-5805
VL - 20
SP - 620
EP - 628
JO - Automation in Construction
JF - Automation in Construction
IS - 5
ER -