Optimization neural network for time series processing
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Дата
2025
Автори
Науковий керівник
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Видавець
National Technical University of Ukraine "Igor Sikorsky Kyiv Polytechnic Institute"
Анотація
The article proposes the architecture of the optimization neural network and the model of test samplesynthesis for the process of extrapolation of time series parameters. In particular, the addition of an inputlayer with the introduction of an optimization scheme of nonlinear trade-offs has been implemented.Extrapolation of the behavior of the time series was carried out according to a test sample, which isformed as a data model with the selection of the trend according to the method of least squares. Thescientific novelty of the results obtained in the article is reflected in the essence of these decisions.The aim of the research is to develop an optimization network architecture and data model forextrapolation, which allows to improve the accuracy and time of predicting the behavior of the time seriesoutside the observation interval. Subject of research: architecture of an artificial neural network andmethods of extrapolation of time series. Object of research: processes of architectural synthesis of anartificial neural network and extrapolation of time series behavior outside the observation interval.The optimization layer provides mini-requirements for the approximation of training and test samples.This is especially appropriate for time series with stochastic noise and allows you to reduce the impactof random errors on time series prediction results. The use of model data for extrapolation allows you todetermine the behavior of the time series outside the observation interval. At the same time, the forecastingtime with acceptable accuracy characteristics increases. These solutions are reflected in the name of theoptimization neural network, which is proposed by the authors. The study of the effectiveness of the proposedsolutions was implemented by methods of simulation modeling on a modified artificial neural network. Theresults of the calculations proved an increase in the adequacy of data models and an increase in the accuracyof extrapolation.
Опис
Ключові слова
mathematical model, multi-criteria optimization, time series, artificial neural network, математична модель, багатокритеріальна оптимізація, часовий ряд, штучна нейронна мережа
Бібліографічний опис
Pysarchuk, O. Optimization neural network for time series processing / Oleksii Pysarchuk, Danylo Baran // Information, Computing and Intelligent systems. – 2025. – No. 7. – P. 39-48. – Bibliogr.: 10 ref.