Investigation of combined ensemble methods for diagnostics of the quality of interaction of human-machine systems

Authors:

Oleksandr Laktionov*, orcid.org/0000-0002-5230-524X, National University “Yuri Kondratyuk Poltava Polytechnic”, Poltava, Ukraine, e-mail: This email address is being protected from spambots. You need JavaScript enabled to view it.

Leonid Lievi, orcid.org/0000-0003-4619-8764, National University “Yuri Kondratyuk Poltava Polytechnic”, Poltava, Ukraine, e-mail: This email address is being protected from spambots. You need JavaScript enabled to view it.

Andrii Tretiak, orcid.org/0000-0003-3971-3078, National University “Yuri Kondratyuk Poltava Polytechnic”, Poltava, Ukraine, e-mail: This email address is being protected from spambots. You need JavaScript enabled to view it.

Mykola Movin, orcid.org/0000-0002-7470-6482, National University “Yuri Kondratyuk Poltava Polytechnic”, Poltava, Ukraine, e-mail: This email address is being protected from spambots. You need JavaScript enabled to view it.

* Corresponding author e-mail This email address is being protected from spambots. You need JavaScript enabled to view it.

повний текст / full article

Naukovyi Visnyk Natsionalnoho Hirnychoho Universytetu. 2023, (4): 138 - 143

https://doi.org/10.33271/nvngu/2023-4/138

Abstract:

Purpose. Study on the process of combining several methods for determining the quality indices of human-machine interaction, containing various configurations for determining the weight coefficients in an ensemble.

Methodology. The process of diagnosing the quality of the interaction of a human-machine system with four elements of subsystems is studied using the example of the system “Operator–Machining Center – Control Program – Safe Environment”. The main hypothesis of the study is the combination of several methods for determining the quality indices of human-machine interaction, containing different configurations for determining the weight coefficients in the ensemble. A combined method for diagnosing the quality of interaction between human-machine systems based on ensemble models, which include non-ensemble ones, has been proposed. The ensemble index has been determined by averaging the non-ensemble indices. The defined ensemble indices and element scores of the four subsystems are used as input scores to a multiple regression model to generate prediction.

Findings. Four combinations of ensemble indices have been developed and implemented in software, which are characterized by a minimum value of the standard deviation compared to the existing ones. According to the results of experimental verification, the proposed models demonstrate the value of the standard deviation of 0.1404; 0.1401; 0.1411; 0.1397, and the existing ones are 0.1532; 0.1535; 0.1532; 0.1532.

Originality. The combined ensemble method for diagnosing the quality of interaction between elements of subsystems takes into account linear models with non-linear variables and different ways of determining weight coefficients.

Practical value. The scenario for the practical use of the results obtained is a possible option for optimizing production, where, depending on the final result, specialists can adjust the value of a particular subsystem to achieve the desired result.

Keywords: ensemble index, averaging model, nonlinear relationship, linear equation, nonlinear transformation, IT-technologies

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