Bobyr, M.V., Emelyanov, S.G., “A nonlinear method of learning neuro-fuzzy models for dynamic control systems”, Applied Soft Computing, 2020, no. 88, 106030
Bobyr M.V., Milostnaya N.A., Kulabuhov S.A., “A method of defuzzification based on the approach of areas ratio”, Applied Soft Computing, 59 (2017), 19-32
Bobyr, M.V., Yakushev, A.S., Dorodnykh, A.A., “Fuzzy devices for cooling the cutting tool of the CNC machine implemented on FPGA”, Measurement: Journal of the International Measurement Confederation, 2020, no. 152, 107378
M. V. Bobyr, S. G. Emelyanov, N. A. Milostnaya, “Optimization of the number of passes in the problem of logical image filtering”, Artificial Intelligence and Decision Making, 2023, no. 2, 98–107
2022
2.
M. Bobyr, A. Arkhipov, S. Gorbachev, J. Cao, S. B. Bhattacharyya, “Fuzzy logic approaches in the task of object edge detection”, Informatics and Automation, 21:2 (2022), 376–404
M. Bobyr, A. Arkhipov, A. Yakushev, “Shade recognition of the color label based on the fuzzy clustering”, Informatics and Automation, 20:2 (2021), 407–434
M. V. Bobyr, A. E. Arkhipov, N. A. Milostnaya, “The method of depth map calculation based on soft operators”, Sistemy i Sredstva Inform., 29:2 (2019), 71–84
M. V. Bobyr, “The method of non-linear learning the neuro-fuzzy inference system”, Artificial Intelligence and Decision Making, 2018, no. 1, 67–75
2016
6.
M. V. Bobyr, S. A. Kulabukhov, N. A. Milostnaya, “Teaching of neuro-fuzzy system on the basis of the method of difference areas”, Artificial Intelligence and Decision Making, 2016, no. 4, 15–26
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