AUTHOR=Garanin Dmitry Anatolyevich , Lukashevich Nikita Sergeevich , Efimenko Sergey Vladimirovich , Chernorutsky Igor Georgievich , Barykin Sergey Evgenievich , Kazaryan Ruben , Buniak Vasilii , Parfenov Alexander TITLE=Reduction of uncertainty using adaptive modeling under stochastic criteria of information content JOURNAL=Frontiers in Applied Mathematics and Statistics VOLUME=8 YEAR=2023 URL=https://www.frontiersin.org/journals/applied-mathematics-and-statistics/articles/10.3389/fams.2022.1092156 DOI=10.3389/fams.2022.1092156 ISSN=2297-4687 ABSTRACT=

Entropy is the concepts from the science of information must be used in the situation where undefined behaviors of the parameters are unknown. The behavior of the casual parameters representing the processes under investigation is a problem that the essay explores from many angles. The provided uniformity criterion, which was developed utilizing the maximum entropy of the metric, has high efficiency and straightforward implementation in manual computation, computer software and hardware, and a variety of similarity, recognition, and classification indicators. The tools required to automate the decision-making process in real-world applications, such as the automatic classification of acoustic events or the fault-detection via vibroacoustic methods, are provided by statistical decision theory to the noise and vibration engineer. Other statistical analysis issues can also be resolved using the provided uniformity criterion.