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  5. Ways of reducing forecast uncertainty in the state of the human neural network modeling

Ways of reducing forecast uncertainty in the state of the human neural network modeling

M.Yu. Burichenko, O.B. Ivanets
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The paper analyzes the sources of uncertainty arising from the construction of models for solving problems of prediction of the diagnostic features of biological objects by means of artificial neural networks. Recommendations for reducing forecast uncertainty at various stages of building a neural network.
Keywords: uncertainty, artificial neural networks, model forecasting, medical and biological parameters, diagnostic signs