Neural network model with fuzzy activation functions for time series predictions

DOI: 10.21293/1818-0442-2016-19-4-49-51

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Abstract: This study develops neural models using fuzzy activation functions to solve the problems of time series predictions. Several fuzzy neural networks with different types of activation function are created. The paper shows the comparison result between the feasibilities of these networks for solving time series prediction problems.

Keywords: fuzzy neural network, fuzzy activation function, membership function, time series predictions

For citation:
Nguen A. T., Korikov A. M. Neural network model with fuzzy activation functions for time series predictions. Doklady Tomskogo gosudarstvennogo universiteta sistem upravleniya i radioelektroniki, 2016, vol. 19, no. 4, pp. 49–51. DOI: 10.21293/1818-0442-2016-19-4-49-51

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