[
1. Abonyi J, Babuska JR, Verbruggen HB, Szeifert F. Incorporating prior knowledge in fuzzy model identification. International Journal of Systems Science. 2000; 31:657-667. doi.org/10.1080/002077200290966.10.1080/002077200290966
]Search in Google Scholar
[
2. Bilenko LF. Zakonomernosti izmelcheniya v barabannyih melnitsah [Regularities of grinding in drum mills]. Moscow: Nedra [in Russian]; 1984.
]Search in Google Scholar
[
3. Bogatikov VN, Kulakov AG. Ispolzovanie gibridnoy neyronnoy seti v raskryitii neopredelennosti funktsii razrusheniya materia-la pri izmelchenii [Application of the hybrid neural network in disclosing ambiguity of the material destruction function in grinding]. Vestnik Kostromskogo gosudarstvennogo universiteta – Bulletin of Kostroma State University. 2006; 11:29-31 [in Russian].
]Search in Google Scholar
[
4. Bogatikov VN, Kulakov AG, Reev SN. Imitatsionnoe modelirovanie tehnologicheskogo protsessa sokrascheniya krupnosti materiala pri izmelchenii v agregate nepreryivnogo deystviya s zamknutyim tsiklom. Informatsionnyie tehnologii v regionalnom razvitii [Simulations of size reduction processes in grinding in the closed-loop continuous unit. Information technologies in regional development]. Apatityi [in Russian]. 2006.
]Search in Google Scholar
[
5. Bublikov A, Tkachov V. Automation of the control process of the mining machines based on fuzzy logic. Naukovyi Visnyk Natsionalnoho Hirnychoho Universytetu. 2019; 3:112‒118.10.29202/nvngu/2019-3/19
]Search in Google Scholar
[
6. Golik V, Komashchenko V, Morkun V, Burdzieva O. Metal deposits combined development experience. Metallurgical and Mining Industry. 2015; 7(6):591-594.
]Search in Google Scholar
[
7. Golik VI, Razorenov YI, Efremenkov AB. Recycling of metal ore mill tailings. Applied Mechanics and Materials. 2014; 682:363-368.10.4028/www.scientific.net/AMM.682.363
]Search in Google Scholar
[
8. Grechnikov AF, Grishanov DG, Pavlov OV, Pushkov AN. Soglasovannoe upravlenie tehnologicheskim kompleksom s posledova-telno soedinennyimi elementami [Cohesive control over a technological comples with sequentially connected elements]. Vestnik Samarskogo gosudarstvennogo aerokosmicheskogo universiteta – Bulletin of Samara State Aerospace University. 2003; 2:29-33 [in Russian].
]Search in Google Scholar
[
9. Gurevich LS. Modelirovanie strukturyi potokov v barabannoy melnitse [Modelling of flow structures in drum mills]. Obogaschenie rud – Ore Concentration. 1989; 2:34-37 [in Russian].
]Search in Google Scholar
[
10. Kafarov VV, Verdiyan MA. Matematicheskie modeli strukturyi potoka materiala v melnitsah [Mathematical models of the structure of material flows in mills]. Moscow: Tsement; 1977. [in Russian].
]Search in Google Scholar
[
11. Kafarov VV, Glebov MB. Matematicheskoe modelirovanie osnovnyih protsessov himicheskih proizvodstv: Uchebnoe posobie dlya vuzov [Mathematical modelling of basic processes of chemical enterprises: Teaching manual for universities]. Moscow: Vysshaya shkola; 1991 [in Russian].
]Search in Google Scholar
[
12. Khmil IV. OsoblivostI tehnologIyi podrIbnennya magnetitovih kvartsitIv v umovah ob’Emnogo nerIvnomIrno-komponentnogo stisnennya. Dis. kandidata tehn. nauk: 05.15.08 [Peculiarities of grinding technology of magnetite quartzite under volumetric irregular-component compression: Candidate’s thesis (Engineering) 05.15.08]; 2016. [in Ukrainian].
]Search in Google Scholar
[
13. Kramer YB. O kinetike nepreryivnogo izmelcheniya [On kinetics of continuous grinding]. Fiziko-mehanicheskie problemyi razrabotki poleznyih iskopaemyih – Physical and mechanical problems of mineral mining. 1986; 130-131 [in Russian].
]Search in Google Scholar
[
14. Kruglov VV. Iskusstvennyie neyronnyie seti. Teoriya i praktika [Artificial neural networks. Theory and practice]. Moscow: Goryachaya liniya–Telekom; 2001 [in Russian].
]Search in Google Scholar
[
15. Linch AD. Tsiklyi drobleniya i izmelcheniya [Cycles of crushing and grinding]. Moscow: Nedra; 1981 [in Russian].
]Search in Google Scholar
[
16. Maryuta AN, Kachan YG, Bunko VA. Avtomaticheskoe upravlenie tehnologicheskimi protsessami obogatitelnyih fabrik [Automated control over technological processes at cancentrating plants]. Moscow: Nedra; 1981 [in Russian].
]Search in Google Scholar
[
17. Morkun V, Morkun N, Tron V, Hryshchenko S. Synthesis of robust controllers of technological units control systems of ore-dressing factory. Eastern-European Journal of Enterprise Technologies. 2018; 1-2(91):37-47.10.15587/1729-4061.2018.119646
]Search in Google Scholar
[
18. Morkun V, Morkun N, Pikilnyak A. The adaptive control for intensity of ultrasonic influence on iron ore pulp, Metallurgical and Mining Industry. 2014; 6:8-11.
]Search in Google Scholar
[
19. Morkun V, Morkun N, Tron V. Distributed closed-loop control formation for technological line of iron ore raw materials beneficiation. Metallurgical and Mining Industry. 2015; 7:16-19.
]Search in Google Scholar
[
20. Morkun V, Morkun N, Tron V. Distributed control of ore beneficiation interrelated processes under parametric uncertainty, Metallurgical and Mining Industry. 2015; 8:18-21.
]Search in Google Scholar
[
21. Morkun V, Morkun N, Tron V. Identification of control systems for ore-processing industry aggregates based on nonparametric kernel estimators, Metallurgical and Mining Industry. 2015; 1:14-17.
]Search in Google Scholar
[
22. Morkun V, Morkun N, Tron V. Model synthesis of nonlinear nonstationary dynamical systems in concentrating production using Volterra kernel transformation, Metallurgical and Mining Industry. 2015; 10:6-9.
]Search in Google Scholar
[
23. Morkun V, Tron V. Automation of iron ore raw materials beneficiation with the operational recognition of its varieties in process streams, Metallurgical and Mining Industry. 2014; 6: 4-7.
]Search in Google Scholar
[
24. Olііnуk TA. Doslidzhennia vplivu dinamIchnih efektIv visokoenergetichnogo ultrazvuku na gazovi bulbashky u pulpI dlya upravlInnya parametrami yiyi gazovoi fazy u protsesi flotatsii: zvIt pro NDR [Investigation into dynamic effects of high-energy ultrasound on gas bubbles in slurry to control parameters of its gas phase in floatation: research report]. DVNZ «KrivorIzkiy natsIonalniy unIversitet». Kryvyi Rih; 2016 [in Ukrainian].
]Search in Google Scholar
[
25. Pevzner LD, Kostikov VG, Lettiev OA, Kostikov RV. Razrabotka i issledovanie matematicheskoy modeli protsessa rudoizmelche-niya [Development of and investigation into the mathematical model of ore grinding]. Gornyiy informatsionno-analiticheskiy byulleten (nauchnotehnicheskiy zhurnal) – Mining information-analytical bulluten (scientific and technical journal). 2012; 11:312-320 [in Russian].
]Search in Google Scholar
[
26. Porkuian O, Morkun V, Morkun N, Serdyuk O. Predictive control of the iron ore beneficiation process based on the Hammerstein hybrid model, Acta Mechanica et Automatica. 2019; 13(4):262-270.
]Search in Google Scholar
[
27. Porkuian O, Morkun V, Morkun N. Measurement of the ferromagnetic component content in the ore suspension solid phase, Ultrasonics. 2020; 105:106103.
]Search in Google Scholar
[
28. Stupnik N, Kalinichenko V, Pismennij S, Kalinichenko E. Features of underlying levels opening at «ArcelorMittal Krivyi Rih» underground mine. In: New Developments in Mining Engineering 2015: Theoretical and Practical Solutions of Mineral Resources Mining. 2015; 39-44.10.1201/b19901-8
]Search in Google Scholar
[
29. Stupnik M, Kolosov V, Pysmennyi S, Kovbyk K. Selective mining of complex stuctured ore deposits by open stope systems. E3S Web of Conferences. 2019; 123:01007.10.1051/e3sconf/201912301007
]Search in Google Scholar
[
30. Shupov LP. Modelirovanie i raschet na EVM shem obogascheniya [Simulation and computer calculation of concentration schemes]. Moscow: Nedra; 1980 [in Russian].
]Search in Google Scholar
[
31. Takagi T, Sugeno M. Fuzzy identification of systems and its application to modeling and control. IEEE Trans. Systems, Man and Cybernetics. 1985; 15(1):116-132.10.1109/TSMC.1985.6313399
]Search in Google Scholar
[
32. Tihonov ON. Zakonomernosti effektivnogo razdeleniya mineralov v protsessah obogascheniya poleznyih iskopaemyih [Regularities of effective separation of minerals in concentration processes]. Moscow: Nedra; 1984 [in Russian].
]Search in Google Scholar
[
33. Tulleken HJAF. Gray-box modelling and identification using pysical knowledge and Bayesian techniques. Automatica. 1993; 29:285-308.10.1016/0005-1098(93)90124-C
]Search in Google Scholar
[
34. Tuz AA, Sanaeva GN, Prorokov AE, Bogatikov VN. Nechiotkologicheskiy podhod k modelirovaniyu protsessa izmelcheniya v agre-gate nepreryivnogo deystviya s zamknutyim tsiklom Aktsionernogo Obschestva «Kovdorskiy gorno-obogatitelnyiy kombinat» [Fuzzy-logic approach to modelling grinding in the closed-loop continuous unit of the JSC „Kovdor Mining Concentrating Works”]. Internet-zhurnal “NAUKOVEDENIYE” – Internet-journal “SCIENCE STUDIES”. 2016; 8(1). https://cyberleninka.ru/article/n/nechyotko-logicheskiy-podhod-kmodelirovaniyu-protsessa-izmelcheniya-v-agregate-nepreryvnogodeystviya-s-zamknutym-tsiklom [in Russian].
]Search in Google Scholar
[
35. Tuz AA, Sanayeva GN, Prorokov AY, Bogatikov VN. Upravlenie tehnologicheskimi protsessami izmelcheniya i osnovnyie napravleniya ih avtomatizatsii [Control over grinding processes and basic trends of their automation]. Vestnik evraziyskoy nauki – Bulletin of Eurasian Science. 2016; 8(2):130–131 [in Russian].
]Search in Google Scholar
[
36. Zlatorunskaya GE. Otsenka izmelchaemosti droblenoy rudyi po ee granulometricheskoy harakteristike [Assessment of ground ore by its granulometric characteristic]. Obogaschenie rud – Ore Concentration. 1985; 2 [in Russian].
]Search in Google Scholar
[
37. Zolotkov NF, Dyomin VT, Kontsevoy AV, Smirnov SV. Modernizatsiya i razvitie sistem avtomatizirovannogo kontrolya i upravleniya [Updating and development of automated control systems]. Gornyi zhurnal – Mining Journal. 2012; 10:91-96 [in Russian].
]Search in Google Scholar
, 