Predictive analysis in industry Echkina, Eugenia; Levichev, Alexander; Sushko, Andrey
Journal of physics. Conference series,
02/2024, Letnik:
2701, Številka:
1
Journal Article
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Predictive analytics is a field of knowledge that allows you to make informed decisions, prepare for unforeseen situations and anticipate all kinds of emergencies. Recently, predictive analysis has ...been actively used in industry: based on historical data, the model makes a probabilistic forecast of the device’s behavior in the near future. This paper provides a comparative analysis of two predictive models, which both could self-learn and had the property of self-correction. The accuracy of predicting the development of a defect in industrial equipment, as well as the prediction horizon, were evaluated. Particular attention is paid to the peculiarity of working with data obtained from production sensors.
This paper presents a methodological review of models for predicting blood glucose (BG) concentration, risks and BG events. The surveyed models are classified into three categories, and they are ...presented in summary tables containing the most relevant data regarding the experimental setup for fitting and testing each model as well as the input signals and the performance metrics. Each category exhibits trends that are presented and discussed. This document aims to be a compact guide to determine the modeling options that are currently being exploited for personalized BG prediction.
This paper presents a methodological review of models for predicting blood glucose (BG) concentration, risks, and BG events. The surveyed models are classified into three categories, and they are presented in summary tables containing the most relevant data regarding the experimental setup for fitting and testing each model as well as the input signals and the performance metrics. Each category exhibits trends that are presented and discussed. This document aims to be a compact guide to determine the modeling options that are currently being exploited for personalized BG prediction.
LINKED CONTENT
This article is linked to Brandman et al papers. To view these articles, visit https://doi.org/10.1111/apt.16874 and https://doi.org/10.1111/apt.16972
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