Design assessments of complex systems based on design oriented modelling and uncertainty analysis

Yu, Chao; Zhu, Yunpeng; Luo, Haitao; Zhang, Luo; Li, Lei

doi:10.1016/j.ymssp.2022.109988

Cited by 6 publications

(4 citation statements)

References 27 publications

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“…In all series of estimates of ensemble indices, two anomalous val ues were found (system 197 and system 224, which have pri mary estimates 4; 5; 5; 5 and 5; 5; 5; 4; 5), what in turn af fected the size of the updated experimental sample (n 21 = = 248 selection systems).The ensemble indices, in a certain experimental way, are characterized by the support of the condition of normal distri bution. This is evidenced by the calculation results of the Kol mohorovSmyrnov criterion for the indices4 , 0635; 0.0621; 0.0645; 0.0624 at р > 0.2.In Table…”

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confidence: 68%

“…On the basis of the standard deviation, the proposed ensem ble indices have an advantage over the existing ones. Thus, the standard deviation of the proposed ensemble indices 4 Conclusions. The task of developing a mathematical model connecting the subsystem elements and weight coefficients has been solved by using a linear equation with nonlinear trans formations of input variables.…”

Section: Tablementioning

confidence: 97%

“…The bias problem is resolved through the use of complex indicators of humanmachine systems [4]. Solving displace ment problems is a wellknown practice, and there are un solved problems in diagnosing the quality of interaction be tween elements of subsystems [5].…”

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confidence: 99%

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

Laktionov,

Lievi,

Tretiak

et al. 2023

Nauk. visn. nat. hirn. univ.

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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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confidence: 68%

Section: Tablementioning

confidence: 97%

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

Laktionov,

Lievi,

Tretiak

et al. 2023

Nauk. visn. nat. hirn. univ.

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“…For a given detection method, errors inevitably exist, as elucidated in the previous sections regarding the random errors of this system. Therefore, uncertainty assessment is necessary [13]. Uncertainty indicates the reliability of results and serves as a metric for the quality of results.…”

Section: Analysis Of System Characterization Indicators and Detection...mentioning

confidence: 99%

A Capacitive Transparent Liquid Concentration Detecting System Based on LabVIEW

Shangguan,

Cui,

Liang

et al. 2024

HSET

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The accurate detection of transparent liquid concentrations holds widespread applications in production and daily life, making the design and development of novel detection systems crucial. In this study, a capacitance-based detection system for measuring the concentration of transparent liquids was successfully designed and implemented. The system utilized a cylindrical capacitive sensor and FDC2214 module for capacitance measurement, with data acquisition, processing, and display accomplished through an Arduino microcontroller and a LabVIEW program. The results of practical detections demonstrate that the developed system exhibits advantages such as non-contact operation, low cost, high accuracy, minimal sample requirement, and rapid detection speed. This system effectively meets the demands for transparent liquid concentration detection.

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