TY - GEN
T1 - Influence of feature extraction duration and step size on ANN based multisensor fire detection performance
AU - Wang, Xue-Gui
AU - Lo, Siu-Ming
AU - Zhang, He-Ping
PY - 2013
Y1 - 2013
N2 - ANN has displayed great advantage in multisensor based fire detection. One of the major application steps in application of ANN in multisensor fire detection is feature extraction of time series. The objective of this research is to investigate feature extraction window duration and step size on fire detection performance. Some experimental results are adopted as benchmark tests, and detected fire time and failed alarm rate are the important indicators of performances. Three ANN types, namely BP, RBF and PNN are analyzed. Results indicate that both observation window duration and step size can determine ANN fire detection performance to a large extent, and a duration period of 90s with time step varies from 25s to 200s is recommended. Meanwhile, PNN might be the favorable ANN types related to the two performance parameters. © 2013 The Authors. Published by Elsevier Ltd.
AB - ANN has displayed great advantage in multisensor based fire detection. One of the major application steps in application of ANN in multisensor fire detection is feature extraction of time series. The objective of this research is to investigate feature extraction window duration and step size on fire detection performance. Some experimental results are adopted as benchmark tests, and detected fire time and failed alarm rate are the important indicators of performances. Three ANN types, namely BP, RBF and PNN are analyzed. Results indicate that both observation window duration and step size can determine ANN fire detection performance to a large extent, and a duration period of 90s with time step varies from 25s to 200s is recommended. Meanwhile, PNN might be the favorable ANN types related to the two performance parameters. © 2013 The Authors. Published by Elsevier Ltd.
KW - Artificial neuron network
KW - Dynamic observation window
KW - Multisensor fire detection
KW - Step size
UR - http://www.scopus.com/inward/record.url?scp=84891693901&partnerID=8YFLogxK
UR - https://www.scopus.com/record/pubmetrics.uri?eid=2-s2.0-84891693901&origin=recordpage
U2 - 10.1016/j.proeng.2013.02.162
DO - 10.1016/j.proeng.2013.02.162
M3 - RGC 32 - Refereed conference paper (with host publication)
SN - 9781627481632
VL - 52
SP - 413
EP - 421
BT - Procedia Engineering
T2 - 2012 International Conference on Performance-Based Fire and Fire Protection Engineering
Y2 - 17 October 2012 through 19 October 2012
ER -