UDC 622.862.3 : 004.42


Slashchov A.I., Doctoral Student

(IGTM NAS of Ukraine)


The article presents results of study of intelligent fuzzy logic algorithms developed on the basis of fuzzy logic methods for information system of the mine safety system with taking into account total assessment, operational forecasting and possible scenarios of geomechanical development.

In order to prevent emergency situations caused by the lost geotechnical system stability due to the uncertain behavior of the rock mass, a new fuzzy controller was designed which could generate an additional control signal. For the fuzzy controller, methods of data fuzziness, inference and de-fuzziness were validate, and linguistic rules were designed in order to control parameters of the geotechnical system. With the help of the Cauchy problem solved by Runge-Kutta method of the 4th order, the Matlab designed a  software model of the proposed system which simulated the system operation. The model has proved operability and static stability of the developed  algorithms. Output signal of the fuzzy controller can be used as information for estimating risk for geotechnical systems, preventing possible emergency situations and, consequently, can improve job safety in the mines.

Keywords: geotechnical system, geomechanical processes, job safety, information technology, intelligent algorithms, fuzzy logic.


1. Zadeh, L.A. et al. (1996), Fuzzy Sets, Fuzzy Logic, Fuzzy Systems, World Scientific Press, London, UK, ISBN 981-02-2421-4.

2. Zadeh, Lotfi Asker (1996),  Fuzzy Sets, Fuzzy Logic, and Fuzzy Systems: Selected Papers by Lofti A. Zadeh (Advances in Fuzzy Systems - Applications & Theory), in George J. Klir & Bo Yuan. (ed.), World Scientific Publishing Co Pte Ltd, London, UK.

3. Robert, V.Demicco (ed.) and George, J.Klir (ed.) (2003), Fuzzy Logic in Geology 1st Edition, Academic Press, London, UK, ISBN 9780080521893.

4. Montagna, F. (2001), “Three complexity problems in quantified fuzzy logic”, Studia Logica, vol. 68, рр. 143-152.

5. Fermüller, C.G. (2003), “Theories of vagueness versus fuzzy logic: can logicians learn from philosophers?”, Neural Network World, vol. 13, pp. 455-465.

6. Shevchenko, V.G. and Slashchov, A.I. (2014), “Development of schemes and algorithms of functioning information complex personnel management for uranium mines”, Geotekhnicheskaya Mekhanika [Geo-Technical Mechanics], no. 117, pp. 128-140, UA.

7. Slashchov, A.I. (2011), “Development of mobile technology for personnel management at enterprises in the mining”, Geotekhnicheskaya Mekhanika [Geo-Technical Mechanics], no. 95, pp. 142-149, UA.

8. Kalashnikov, V.I. Palis, F. and Lozynskyy, O.YU. (2000), “Osnovy teoriyi fazy-lohiky ta fazy-rehulyuvannya”, Donetsk : Magdeburg : Lviv, UA.

About the authors:

Slashchov Anton Igorevich, Master of Science, Doctoral Student, M.S. Polyakov Institute of Geotechnical Mechanics under the National Academy of Science of Ukraine (IGTM, NASU), Dnepropetrovsk, Ukraine, Этот адрес электронной почты защищен от спам-ботов. У вас должен быть включен JavaScript для просмотра.