DocumentCode
2426977
Title
Fire Risk Evaluation Model of High-Rise Buildings Based on Multilevel BP Neural Network
Author
Xia, Dengyou
Author_Institution
Chinese People´´s Armed Police Force Acad., Langfang
Volume
4
fYear
2007
fDate
24-27 Aug. 2007
Firstpage
436
Lastpage
441
Abstract
On the basis of establishing the fire risk evaluation index system and their standard values of high-rise buildings, a multilevel BP neural network model is developed. The model can solve the problem of uncertainty, fuzziness and dynamic complexity well in the process of fire risk evaluation, which makes evaluation result more practicable and scientific. Exemplified case study has shown that the reliable evaluation result could be obtained in shorter time as long as the values of related fire risk evaluation indexes are input into the model. And the evaluation result accords with the actual situation and that of fuzzy evaluation by fire experts.
Keywords
backpropagation; computational complexity; fires; fuzzy set theory; neural nets; risk management; structural engineering computing; dynamic complexity; fire risk evaluation model; fuzziness complexity; high-rise buildings; index system; multilevel BP neural network; Artificial neural networks; Biological neural networks; Buildings; Fires; Fuzzy sets; Neural networks; Neurons; Safety devices; Standards development; Uncertainty;
fLanguage
English
Publisher
ieee
Conference_Titel
Fuzzy Systems and Knowledge Discovery, 2007. FSKD 2007. Fourth International Conference on
Conference_Location
Haikou
Print_ISBN
978-0-7695-2874-8
Type
conf
DOI
10.1109/FSKD.2007.291
Filename
4406427
Link To Document