EDP Sciences logo
Web of Conferences logo
Search
Menu
All issues Volume 201 (2020) E3S Web Conf., 201 (2020) 01030 References
Open Access
Issue
E3S Web Conf.
Volume 201, 2020
Ukrainian School of Mining Engineering - 2020
Article Number 01030
Number of page(s) 10
DOI https://doi.org/10.1051/e3sconf/202020101030
Published online 23 October 2020
  1. Khorolskyi, A., & Hrinov, V. (2020). Otsinka i vybir parametriv pry rozrobtsi rodovyshch korysnykh kopalyn. Fyziko-tekhnycheskie problemy hornoho proizvodstva, (22), 118-140. https://doi.org/10.37101/ftpgp22.01.009 [Google Scholar]
  2. Kursunoglu, N., & Onder, M. (2015). Selection of an appropriate fan for an underground coal mine using the Analytic Hierarchy Process. Tunnelling and Underground Space Technology, (48), 101-109. [CrossRef] [Google Scholar]
  3. Ataei, M., Jamshidi, M., Sereshki, F., & Jalali, I. (2008). Mining method selection by AHP approach. Journal of the Southern African Institute of Mining and Metallurgy, 108(12),741-749. [Google Scholar]
  4. Bogdanovic, D., Nikolic, D., & Ilic, I. (2012). Mining method selection by integrated AHP and PROMETHEE method. Anais da Academia Brasileira de Ciencias, 84(1),219-233. [CrossRef] [PubMed] [Google Scholar]
  5. Iphar, M., & Alpay, S. (2019). A mobile application based on multi-criteria decision-making methods for underground mining method selection. International Journal of Mining, Reclamation and Environment, 33(7),480-504. [Google Scholar]
  6. Hayati, M., Rajabzadeh, R., & Darabi, M. (2015). Determination of Optimal Block Size in Angouran Mine Using VIKOR Method. Journal of Materials and Environmental Science, 6(11),3236-3244. [Google Scholar]
  7. Huang, W. et al. (2015). Stability assessment of underground mined-out areas in a gold mine based on complex system theory. Geotechnical and Geological Engineering, 33(5),1295-1305. [CrossRef] [Google Scholar]
  8. Naghadehi, M.Z., Mikaeil, R., & Ataei, M. (2009). The application of fuzzy analytic hierarchy process (FAHP) approach to selection of optimum underground mining method for Jajarm Bauxite Mine, Iran. Expert Systems with Applications, 36(4), 8218-8226. [Google Scholar]
  9. Balusa, B., & Singam, J. (2018). Underground mining method selection using WPM and PROMETHEE. Journal of the Institution of Engineers (India): Series D, 99(1),165-171. [CrossRef] [Google Scholar]
  10. Hrinov, V. & Khorolskyi, A. (2018). Improving the Process of Coal Extraction Based on the Parameter Optimization of Mining Equipment. E3S Web of Conferences, (60), 00017. https://doi.org/10.1051/e3sconf/20186000017 [CrossRef] [EDP Sciences] [Google Scholar]
  11. Kulshreshtha, M., & Parikh J. (2002). Study of efficiency and productivity growth in opencast and underground coal mining in India: a DEA analysis. Energy Economics, 24(5),439-453. [Google Scholar]
  12. Li, P. et al. (2011). Time series prediction of mining subsidence based on a SVM. Mining Science and Technology, 21(4), 557-562. [Google Scholar]
  13. Bakhtavar, E., Shahriar, K., & Mirhassani, A. (2012). Optimization of the transition from open-pit to underground operation in combined mining using (0-1) integer programming. Journal of the Southern African Institute of Mining and Metallurgy, 112(12),1059-1064. [Google Scholar]
  14. Erdogan, G. et al. (2017). Implementation and comparison of four stope boundary optimization algorithms in an existing underground mine. International Journal of Mining, Reclamation and Environment, 31(6), 389-403. [CrossRef] [Google Scholar]
  15. Dimitrakopoulos, R., & Ramazan, S. (2008). Stochastic integer programming for optimising long term production schedules of open pit mines: methods, application and value of stochastic solutions. Mining Technology, 117(4),155-160. [CrossRef] [Google Scholar]
  16. Khorolskyi, A., Hrinov, V., & Kaliushenko, O. (2019). Network models for searching for optimal economic and environmental strategies for field development. Procedia Environmental Science, Engineering and Management, 6(3),463-471. [Google Scholar]
  17. Fomychov, V., Mamaikin, O., Demchenko, Y., Prykhorchuk, O., & Jarosz, J. (2018). Analysis of the efficiency of geomechanical model of mine working based on computational and field studies. Mining of Mineral Deposits, 12(4),46-55. https://doi.org/10.15407/mining12.04.046 [CrossRef] [Google Scholar]
  18. Saik, P., Petlovanyi, M., Lozynskyi, V., Sai, K., & Merzlikin, A. (2018). Innovative Approach to the Integrated Use of Energy Resources of Underground Coal Gasification. Solid State Phenomena, (277), 221-231. https://doi.org/10.4028/www.scientific.net/ssp.277.221 [CrossRef] [Google Scholar]
  19. Sadovenko, I., Inkin, O., Dereviahina, N., & Hriplivec, Y. (2018). Analyzing the parameters influencing the efficiency of undereground coal gasification. Journal of Geology, Geography and Geoecology, 27(2),332-336. https://doi.org/10.15421/111857 [CrossRef] [Google Scholar]
  20. Sadovenko, I., Puhach, A., & Dereviahina, N. (2019). Investigation of hydrogeomechanical parameters of loess massifs in conditions of technogenic underflooding and development of technical recommendations for strengthening of bases of foundations. Journal of Geology, Geography and Geoecology, 28(1),173-179. https://doi.org/10.15421/111918 [CrossRef] [Google Scholar]
  21. Salli, S., Pochepov, V., & Mamaykin, O. (2014). Theoretical aspects of the potential technological schemes evaluation and their susceptibility to innovations. Progressive Technologies of Coal, Coalbed Methane, and Ores Mining, 491-496. https://doi.org/10.1201/b17547-81 [Google Scholar]
  22. Khorolskyi, A., Hrinov, V., & Mamaikin, O. (2019). Models and methods to make decisions while mining production scheduling. Mining of Mineral Deposits, 13(4),53-62. https://doi.org/10.33271/mining13.04.053 [CrossRef] [Google Scholar]
  23. Hrinov, V., & Khorolskyi, A. (2019). Optymalne proektuvannia parametriv hirnychozbahachuvalnykh pidpryiemstv dlia ratsionalnoho osvoiennia tsinnykh rodovyshch Ukrainy. Fiziko-tekhnicheskie problemy hornoho proizvodstva, (21), 128-145.https://doi.org/10.37101/ftpgp21.01.008 [Google Scholar]
  24. Hrinov, V., Khorolskyi, A., & Mamaikin, O. (2019). Dekompozytsiinyi pidkhid pry pobudovi system heneratsii enerhii u vuhlepromyslovykh rehionakh. Visti Donetskoho Hirnychoho Instytutu, (44), 116-126. https://doi.org/10.31474/1999-981x-2019-1-116-126 [Google Scholar]
  25. Bellman, R., & Dreyfus, S. (1965). Prikladnye zadachi dinamicheskogo programmirovaniya. Moskva: Nauka, 460. [Google Scholar]
  26. Hriniov, V., Khorolskyi, A., & Kaliushchenko, O. (2019). Rozroblennia ekolohichnykh stsenariiv efektyvnoho osvoiennia tsinnykh rodovyshch korysnykh kopalyn. Mineralni Resursy Ukrainy, (2), 46-50. https://doi.org/10.31996/mru.2019.2.46-50 [Google Scholar]
  27. Bondarenko, V., Cherniak, V., Cawood, F., & Chervatiuk, V. (2017). Technological safety of sustainable development of coal enterprises. Mining of Mineral Deposits, 11(2),1-11. https://doi.org/10.15407/mining11.02.001 [CrossRef] [Google Scholar]
  28. Kovalevska, I., Zhuravkov, M., Chervatiuk, V., Husiev, O., & Snihur, V. (2019). Generalization of trends in the influence of geomechanics factors on the choice of operation modes for the fastening system in the preparatory mine workings. Mining of Mineral Deposits, 13(3),1-10. https://doi.org/10.33271/mining13.03.001 [CrossRef] [Google Scholar]
  29. Bondarenko, V., Symanovych, G., & Koval, O. (2012). The mechanism of over-coal thin-layered massif deformation of weak rocks in a longwall. Geomechanical Processes During Underground Mining, 41-44. https://doi.org/10.1201/b13157-8 [Google Scholar]
  30. Yeshchenko, M., Koval, V., & Tsvirko, O. (2019). Economic policy priorities of the income regulation. Espacios, 40(38), 11. [Google Scholar]
  31. Baklanova, O., Petrova, M., & Koval, V. (2020). Institutional Transmission in Economic Development. Ikonomicheski Izsledvania, 29(1),68-91. [Google Scholar]

Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.

Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.

Initial download of the metrics may take a while.