Abstract
The paper deals with forecasting time series based on an analysis by neural networks. Any forecasting is primarily aimed to evaluate the trends of changes in some particular factor. The significance of this work is integral to the importance of time series forecasting as a scientific and technical problem. To construct the neural network, we used the PyCharm environment. The work also includes a comparative analysis of the results obtained with the neural network and statistical forecasting methods realised in PyCharm.
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Dzerjinsky, R.I., Mitina, O.A., Dzerzhinskaya, M.K. (2021). Time Series Forecasting Based on Neural Analysis. In: Silhavy, R. (eds) Informatics and Cybernetics in Intelligent Systems. CSOC 2021. Lecture Notes in Networks and Systems, vol 228. Springer, Cham. https://doi.org/10.1007/978-3-030-77448-6_7
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DOI: https://doi.org/10.1007/978-3-030-77448-6_7
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