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2. Bordik I.V., Matafonova T.Yu. Emergency psychological assistance to victims in emergency situations. Moscow: Vodoley-Saut, 2009. 480 p. (In Russ.).
3. Golubeva S.N., Matyushin A.V., Poroshin A.A. Psychological Factors of Panic Origin During Fire and the Grade of the Problem Research. Pozharnaya bezopasnost = Fire Safety. 2006. № 3. pp. 82–87. (In Russ.).
4. Aptukov A.M., Bratsun D.A., Lyushnin A.V. Modeling of Behavior of Panicked Crowd in Multi-Floor Branched Space. Kompyuternye issledovaniya i modelirovanie = Computer Research and Modeling. 2013. Vol. 5. № 3. pp. 491–508. (In Russ.).
5. Helbing D., Farkas I., Vicsek T. Simulating dynamical features of escape panic. Nature. 2000. Vol. 407. pp. 487–490.
6. Moussaida M., Helbing D., Theraulaz G. How simple rules determine pedestrian behavior and crowd disasters. PNAS. 2011. Vol. 108. Iss. 17. pp. 6884–6888.
7. Xu Y., Huang H.J., Yong G. Modified Static Floor Field and Exit Choice for Pedestrian Evacuation. Chinese Physics Letters. 2012. Vol. 29. DOI: 10.1088/0256-307X/29/8/080502
8. Akopov A.S., Beklaryan L.A. Simulation of Human Crowd Behavior in Extreme Situations. International Journal of Pure and Applied Mathematics. 2012. Vol. 79. № 1. pp. 121–138.
9. Abrosimov V.K., Lebidko V.V. Simulation of Mass Events (Illustrated by the XXII Winter Olympic Games 2014). Biznes-informatika = Biznes-Informatika. 2013. № 1 (23). pp. 19–27. (In Russ.).
10. Dauni A. Learning complex systems with Python. Moscow: DMK Press, 2019. 160 p. (In Russ.).
11. Wagner N., Agrawal V. An agent-based simulation system for concert venue crowd evacuation modeling in the presence of a fire disaster. Expert Systems with Applications. 2014. Vol. 41. № 6. pp. 2807–2815.
12. Akopov A.S., Beklaryan L.A. An Agent Model of Crowd Behavior in Emergencies. Automation and Remote Control. 2015. Vol. 76. № 10. pp. 1817–1827.
13. Karashima K., Ohgai A. An Evacuation Simulator for Exploring Mutual Assistance Activities in Neighborhood Communities for Earthquake Disaster Mitigation. International Review for Spatial Planning and Sustainable Development. 2018. Vol. 6. № 1. pp. 18–31.
14. Kalachin S.V. Prediction of Dangerous Fire Factors in a Room by Machine Learning Methods. Bezopasnost truda v promyshlennosti = Occupational Safety in Industry. 2020. № 3. pp. 48–54. (In Russ.). DOI: 10.24000/0409-2961-2020-3-48-54
15. Enikeev M.I. General and social psychology: textbook for universities. Moscow: Norma, Infra-M, 2010. 624 p. (In Russ.).
16. The AnyLogic Company. Available at: https://www.anylogic.com/ (accessed: February 10, 2020).
17. Grigoryev I. AnyLogic 7 in Three Days: A Quick Course in Simulation Modeling. 2 Ed. Scotts Valley: CreateSpace Independent Publishing Platform, 2015. 256 p.
18. Bizli D. Python. Detailed reference. 4-e izd. Saint-Petersburg: Simvol-Plyus, 2010. 864 p. (In Russ.).
19. Vander P.D. Python for сomplex tasks: data science and machine learning. Saint-Petersburg: Piter, 2018. 576 p. (In Russ.).
2. Bordik I.V., Matafonova T.Yu. Emergency psychological assistance to victims in emergency situations. Moscow: Vodoley-Saut, 2009. 480 p. (In Russ.).
3. Golubeva S.N., Matyushin A.V., Poroshin A.A. Psychological Factors of Panic Origin During Fire and the Grade of the Problem Research. Pozharnaya bezopasnost = Fire Safety. 2006. № 3. pp. 82–87. (In Russ.).
4. Aptukov A.M., Bratsun D.A., Lyushnin A.V. Modeling of Behavior of Panicked Crowd in Multi-Floor Branched Space. Kompyuternye issledovaniya i modelirovanie = Computer Research and Modeling. 2013. Vol. 5. № 3. pp. 491–508. (In Russ.).
5. Helbing D., Farkas I., Vicsek T. Simulating dynamical features of escape panic. Nature. 2000. Vol. 407. pp. 487–490.
6. Moussaida M., Helbing D., Theraulaz G. How simple rules determine pedestrian behavior and crowd disasters. PNAS. 2011. Vol. 108. Iss. 17. pp. 6884–6888.
7. Xu Y., Huang H.J., Yong G. Modified Static Floor Field and Exit Choice for Pedestrian Evacuation. Chinese Physics Letters. 2012. Vol. 29. DOI: 10.1088/0256-307X/29/8/080502
8. Akopov A.S., Beklaryan L.A. Simulation of Human Crowd Behavior in Extreme Situations. International Journal of Pure and Applied Mathematics. 2012. Vol. 79. № 1. pp. 121–138.
9. Abrosimov V.K., Lebidko V.V. Simulation of Mass Events (Illustrated by the XXII Winter Olympic Games 2014). Biznes-informatika = Biznes-Informatika. 2013. № 1 (23). pp. 19–27. (In Russ.).
10. Dauni A. Learning complex systems with Python. Moscow: DMK Press, 2019. 160 p. (In Russ.).
11. Wagner N., Agrawal V. An agent-based simulation system for concert venue crowd evacuation modeling in the presence of a fire disaster. Expert Systems with Applications. 2014. Vol. 41. № 6. pp. 2807–2815.
12. Akopov A.S., Beklaryan L.A. An Agent Model of Crowd Behavior in Emergencies. Automation and Remote Control. 2015. Vol. 76. № 10. pp. 1817–1827.
13. Karashima K., Ohgai A. An Evacuation Simulator for Exploring Mutual Assistance Activities in Neighborhood Communities for Earthquake Disaster Mitigation. International Review for Spatial Planning and Sustainable Development. 2018. Vol. 6. № 1. pp. 18–31.
14. Kalachin S.V. Prediction of Dangerous Fire Factors in a Room by Machine Learning Methods. Bezopasnost truda v promyshlennosti = Occupational Safety in Industry. 2020. № 3. pp. 48–54. (In Russ.). DOI: 10.24000/0409-2961-2020-3-48-54
15. Enikeev M.I. General and social psychology: textbook for universities. Moscow: Norma, Infra-M, 2010. 624 p. (In Russ.).
16. The AnyLogic Company. Available at: https://www.anylogic.com/ (accessed: February 10, 2020).
17. Grigoryev I. AnyLogic 7 in Three Days: A Quick Course in Simulation Modeling. 2 Ed. Scotts Valley: CreateSpace Independent Publishing Platform, 2015. 256 p.
18. Bizli D. Python. Detailed reference. 4-e izd. Saint-Petersburg: Simvol-Plyus, 2010. 864 p. (In Russ.).
19. Vander P.D. Python for сomplex tasks: data science and machine learning. Saint-Petersburg: Piter, 2018. 576 p. (In Russ.).