Title :
Fire Risk Evaluation Model of High-Rise Buildings Based on Multilevel BP Neural Network
Author_Institution :
Chinese People´´s Armed Police Force Acad., Langfang
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;
Conference_Titel :
Fuzzy Systems and Knowledge Discovery, 2007. FSKD 2007. Fourth International Conference on
Conference_Location :
Haikou
Print_ISBN :
978-0-7695-2874-8
DOI :
10.1109/FSKD.2007.291