VESTNIK of Samara University. Aerospace and Mechanical EngineeringVESTNIK of Samara University. Aerospace and Mechanical Engineering2542-04532541-7533Samara National Research University2689310.18287/2541-7533-2023-22-3-108-121Research ArticleApproximation of forces of fluid film bearing lubricating layer using machine learning methodsKazakovYu. N.<p>Student</p>KazakYurii@yandex.ruStebakovI. N.<p>Postgraduate Student of the Department of Mechatronics, Mechanics and Robotics</p>chester50796@yandex.ruShutinD. V.<p>Candidate of Science (Engineering), Associate Professor, Department of Mechatronics, Mechanics and Robotics</p>rover.ru@gmail.comSavinL. A.<p>Doctor of Science (Engineering), Professor, Department of Mechatronics, Mechanics and Robotics</p>savin3257@mail.ruOrel State University named after I.S. Turgenev031120232231081210311202303112023Copyright © 2023, VESTNIK of Samara University. Aerospace and Mechanical Engineering2023<p>The article analyzes the application of various machine learning methods for solving the problem of approximating the forces of fluid film bearing lubricating layer in static formulation. The initial data on the values of lubricating layer forces for different shaft positions were obtained using a model of a rotor-bearing system based on the numerical solution of the Reynolds equation, with account for the cavitation effect. Methods for reducing the amount of calculation required to obtain the necessary data set are determined on the basis of analyzing solution approximation accuracy with artificial neural networks. After that, approximation models were constructed using a number of other machine learning methods, and the accuracy of predictions as well as the duration of the training process were analyzed. 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