| DC Field | Value | Language |
|---|
| dc.contributor.author | Titova, Vera | - |
| dc.contributor.author | Gnatchuk, Ielizaveta | - |
| dc.date.accessioned | 2018-02-22T11:50:27Z | - |
| dc.date.available | 2018-02-22T11:50:27Z | - |
| dc.date.issued | 2017 | - |
| dc.identifier.citation | Titova 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.uri | https://ena.lpnu.ua/handle/ntb/39464 | - |
| dc.description.abstract | Formalization 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.language.iso | en | uk_UA |
| dc.publisher | National Technical University «KhPI» | uk_UA |
| dc.subject | formalization of conditions | uk_UA |
| dc.subject | fuzzy neural networks | uk_UA |
| dc.subject | emergency situations | uk_UA |
| dc.subject | problem of classification of emergency situations | uk_UA |
| dc.subject | Formalized Model | uk_UA |
| dc.subject | Neural Network Model | uk_UA |
| dc.title | Evaluation ofa formalized model for classification of emergency situations | uk_UA |
| dc.type | Conference Abstract | uk_UA |
| dc.contributor.affiliation | Khmelnitsky National University | uk_UA |
| dc.coverage.country | UA | uk_UA |
| dc.format.pages | 110-119 | - |
| dc.relation.referencesen | 1. 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.citation.conference | Computational linguistics andintelligent systems (COLINS 2017) | - |
| dc.coverage.placename | Kharkiv | uk_UA |
| Appears in Collections: | Computational linguistics and intelligent systems. – 2017 р.
|
