Evaluation ofa formalized model for classification of emergency situations

dc.citation.conferenceComputational linguistics andintelligent systems (COLINS 2017)
dc.contributor.affiliationKhmelnitsky National Universityuk_UA
dc.contributor.authorTitova, Vera
dc.contributor.authorGnatchuk, Ielizaveta
dc.coverage.countryUAuk_UA
dc.coverage.placenameKharkivuk_UA
dc.date.accessioned2018-02-22T11:50:27Z
dc.date.available2018-02-22T11:50:27Z
dc.date.issued2017
dc.description.abstractFormalization of conditions that characterize the problem of classification of emergency situations is considered in this paper.This formalization is the basis for the Formalized Model of the emergency situations classificationproblem. Intelligent methods are used to solve this problem. These methods are also the basis for the development of the Neural Network Model for emergency situation classification. In this paper wedevelop the structure of the model and determine the number of network layers, the types of neurons and its membership functions. Using the Neural Network Model as decision support for the dispatchers of emergency services makes it possible to improve the quality of emergency situations classification.uk_UA
dc.format.pages110-119
dc.identifier.citationTitova V. Evaluation ofa formalized model for classification of emergency situations / Vera Titova, Ielizaveta Gnatchuk // Computational linguistics andintelligent systems (COLINS 2017) : proceedings of the 1st International conference, Kharkiv, Ukraine, 21 April 2017 / National Technical University «KhPI», Lviv Polytechnic National University. – Kharkiv, 2017. – P. 110–119. – Bibliography: 8 titles.uk_UA
dc.identifier.urihttps://ena.lpnu.ua/handle/ntb/39464
dc.language.isoenuk_UA
dc.publisherNational Technical University «KhPI»uk_UA
dc.relation.referencesen1. Michael N. DeMers. Fundamentals of geographic information systems. 4th ed. – Hoboken, NJ : Wiley, 2009 – pp. 1-443. 2. V. Seredovych. Geoinformatsionnyie sistemyi (naznachenie, funktsii, klassifikatsiya)/ V. Seredovych, V. Klyushnychenko, N. Tymofeeva. – Novosibirsk: SGGA, 2008. – pp. 1- 192. [in Russian] 3. Ya.Bedriy.Bezpekazhyttyediyal'nosti. – L'viv: Vydavnycha firma «Afisha», 1998. – pp. 1- 298. [in Ukrainian] 4. V. Lokazyuk. Intelektual'ne diahnostuvannya mikroprotsesornykh prystroyiv ta system/ V. Lokazyuk, O. Pomorova, A. Dominov. – Kyyiv: "Takispravy", 2001. – pp. 1-286. [in Ukrainian] 5. J. Hawkins. On Intelligence /J. Hawkins,S. Blakeslee. – New York, NY: Owl Books, 2005. – pp. 1-262. 6. Kruglov V. Nechetkaya logika i iskusstvennyie neyronnyie seti/ V. Kruglov, M. Dli, R. Golunov. – M.: FIZMATLIT, 2001. – pp. 1-201. [in Russian] 7. V. Titova. Realizatsiya nechitkoyi neyronnoyi merezhi dlya rozpiznavannya nadzvychayny khsytuatsiy u paketi Matlab. / Proceedings of international scientific conference "Theoretical and applied aspects of program systems development – 2014", Kyyiv, 2014. – pp. 231-238. [in Ukrainian] 8. N. Nazarov. Metrologiya. Osnovnyie ponyatiya i matematicheskie modeli. – M.: Vyisshayashkola, 2002. — pp. 1-352. [in Russian]uk_UA
dc.subjectformalization of conditionsuk_UA
dc.subjectfuzzy neural networksuk_UA
dc.subjectemergency situationsuk_UA
dc.subjectproblem of classification of emergency situationsuk_UA
dc.subjectFormalized Modeluk_UA
dc.subjectNeural Network Modeluk_UA
dc.titleEvaluation ofa formalized model for classification of emergency situationsuk_UA
dc.typeConference Abstractuk_UA

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