KnE Engineering

ISSN: 2518-6841

The latest conference proceedings on all fields of engineering.

Information and Analytical Support for Management of Fire Extinguishing at Highly Dangerous and Technically Complex Facilities

Published date:May 07 2018

Journal Title: KnE Engineering

Issue title: Russian Forum of Young Scientists (RFYS)

Pages:229–237

DOI: 10.18502/keg.v3i4.2246

Authors:
Abstract:

In this article the authors formulate the task for process management of man-made fire extinguishing at highly dangerous and technically complex facilities. This task consists of fire localization and elimination using minimal assignment in minimum amount of time. For this task the authors developed a neuro-fuzzy model for fire extinguishing process control, the main elements of which are a neuro-fuzzy model for predicting the fire area, a neuro-fuzzy model for selecting the fire rank, a neuro-fuzzy model for evaluating the implementation success of the plan, a neuro-fuzzy model for selecting the optimal action plan, an analytical model for evaluation of resources sufficiency, an analytical model for resources selection, and a model for implementation of neuro-fuzzy models. In comparison with existing models, distinctive features of the developed model are the following: application of combined (bell-shaped with thresholds) membership functions that allow to perform
more accurate approximation of input parameters values; implementation of the block to eliminate dynamic errors. This paper assesses model adequacy through verification and validation. The authors developed a system for fire extinguishing process control. This system allows us to raise of firefighters’ efficiency due to increase of accuracy of managerial decisions taken by the manager and time reduction needed to formulate
a decision.

References:

[1] Matyushin A V 2016 Fires and fire safety in 2015: Statistical compilation FSRI (Moscow) 124.


[2] Stankevich Т S 2016 Information and analytical support for fire extinguishing process control in seaports: dis. PhD Eng. FSA of EMERCOM of Russia (Moscow) 172.


[3] Teterin I M, Topolskiy N G, Klimovtsov V M and Prus Y V 2008 Use of support systems of decision-making by the managers of operational departments in case of fire extinguishing in large cities Techn. of technosph. saf.4 (20) 1-21.


[4] Butuzov S Y, Korobko V B, Pranov B M, Stankevich Т S and Chlenov A N 2016 A neuro-fuzzy model of support for fire extinguishing control in seaports Contr. syst. and inform. technol.4 (66) 91-6.


[5] Jang J S R 1993 ANFIS: Adaptive-network-based fuzzy inference systems IEEE Transact. on SMC 3665-84.


[6] Gliwa B and Byrski A 2011 Hybrid neuro-fuzzy classifier based on NEFCLASS model Comp. Scien.12 115-35.


[7] Stankevich T S and Kiper A V 09.17.2012 Classifier of fire ranks Certif. of the stat. registr. of comp. progr. No.2012618426 9 (71) 1.


[8] Stankevich T S and Kiper A V 12.18.2013 Intellectual decision support system based on fuzzy neural networks for fire extinguishing manager in the territory of “Kaliningrad Commercial Seaport” OJSC Certif. of the stat. registr. of comp. progr. No. 2013661903 12 (86) 1.

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