Ensembles of Neural Network Classifiers in the Problem of Analyzing Telemetry Information Data of a Small Spacecraft
https://doi.org/10.17586/0021-3454-2024-67-11-943-950
Abstract
The problem of classification analysis of time series data of telemetry information of a small spacecraft is considered in order to determine its technical state. Results of development and research of ensemble models of hybrid neural network classifiers based on ensembles such as bagging and AdaBoost, are presented. The basic model of a hybrid neural network classifier, obtained by automatic search using a genetic algorithm for searching hybrid neural network classifiers, is considered. This neural network model makes it possible to build and train a bagging model of an ensemble of hybrid neural network classifiers, the quality of which exceeds both the quality of the basic neural network model and the quality of ensembles of classifiers such as Random Forest, Bagging, Gradient Boosting, Adaptive Boosting (AdaBoost), Histogram-based Gradient Boosting based on decision trees.
About the Author
V. Yu. Skobtsov
St. Petersburg State University of Aerospace Instrumentation; St. Petersburg Institute for Informatics and Automation of the RA
Russian Federation
Russian Federation
Vadim Yu. Skobtsov — PhD, Associate Professor; Department of Computer Technology and Software
Engineering; Associate Professor; Laboratory of Information Technologies in the System Analysis and Modeling; Senior Researcher
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For citations:
Skobtsov V.Yu. Ensembles of Neural Network Classifiers in the Problem of Analyzing Telemetry Information Data of a Small Spacecraft. Journal of Instrument Engineering. 2024;67(11):943-950. (In Russ.) https://doi.org/10.17586/0021-3454-2024-67-11-943-950
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