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

Oleksandr Laktionov, Leonid Lievi, A. Tretiak, Mykola Movin
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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.
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人机系统交互质量诊断的组合集成方法研究
意图研究将几种确定人机交互质量指标的方法相结合的过程,包括确定集合中权重系数的各种配置。方法论以“操作员-加工中心-控制程序-安全环境”系统为例,研究了人机系统与四个子系统交互质量的诊断过程。该研究的主要假设是确定人机交互质量指标的几种方法的组合,包括确定集合中权重系数的不同配置。提出了一种基于集成模型(包括非集成模型)的人机交互质量综合诊断方法。系综索引是通过对非系综索引取平均值来确定的。四个子系统的定义的集合指数和元素得分被用作多元回归模型的输入得分,以生成预测。调查结果。已经开发了四种综合指数组合,并在软件中实现,其特征是与现有指数相比标准偏差最小。根据实验验证结果,所提出的模型的标准偏差值为0.1404;0.1401;0.1411;0.1397,现有为0.1532;0.1535;0.1532;0.1532.独创性。用于诊断子系统元素之间相互作用质量的组合集成方法考虑了具有非线性变量的线性模型和确定权重系数的不同方法。实用价值。实际使用所获得结果的场景是优化生产的一种可能选择,根据最终结果,专家可以调整特定子系统的值,以实现所需结果。
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CiteScore
1.70
自引率
0.00%
发文量
148
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