Intelligent security systems engineering for modeling fire critical incidents: Towards sustainable security
Ali Asgary , Ali Sadeghi Naini , Jason Levy
Journal of Systems Science and Systems Engineering ›› 2009, Vol. 18 ›› Issue (4) : 477 -488.
Intelligent security systems engineering for modeling fire critical incidents: Towards sustainable security
An intelligent security systems engineering approach is used to analyze fire and explosive critical incidents, a growing concern in urban communities. A feed-forward back-propagation neural network models the damages arising from these critical incidents. The overall goal is to promote fire safety and sustainable security. The intelligent security systems engineering prediction model uses a fully connected multilayer neural network and considers a number of factors related to the fire or explosive incident including the type of property affected, the time of day, and the ignition source. The network was trained on a large number of critical incident records reported in Toronto, Canada between 2000 and 2006. Our intelligent security systems engineering approach can help emergency responders by improving critical incident analysis, sustainable security, and fire risk management.
Intelligent security / systems engineering / fire / feed-forward neural networks / critical incidents
| [1] |
Battiti, R. & Masulli, F. (1990). BFGS optimization for faster and automated supervised learning. In: Proceedings of the International Neural Network Conference, 757–760, Paris |
| [2] |
|
| [3] |
|
| [4] |
Council of Canadian Fire Marshals and Fire Commissioners (CCFM-FC). (2007). Fire losses in Canada. Annual Report 2002 |
| [5] |
Critical Incident Analysis Group (CIAG). (2009). University of Virginia. Available via DIALOG. http://www.healthsystem.virginia.edu/internet/ciag/ |
| [6] |
Gurney, K. (1997). An Introduction to Neural Networks. Routledge, London |
| [7] |
|
| [8] |
Haykin, S. (1999). Neural Networks: A Comprehensive Foundation. Prentice Hall |
| [9] |
|
| [10] |
|
| [11] |
|
| [12] |
National Center for Critical Incident Analysis (NCCIA) (2009). National Defense University. Available via DIALOG. http://www.criticalincident.org/index.html |
| [13] |
|
| [14] |
|
| [15] |
|
| [16] |
|
| [17] |
|
| [18] |
Xia, D. (2007). Fire risk evaluation model of high-rise buildings based on multilevel BP neural network. In: Fourth International Conference on Fuzzy Systems and Knowledge Discovery (FSKD), Haikou, Hainan, China, 2007 |
| [19] |
|
/
| 〈 |
|
〉 |