COMPARISON OF THE ACCURACY OF FORECASTING THE VALUE OF THE COMPANY'S SHARES USING A CONVOLUTION NEURAL NETWORK (CNN), A SIMPLE RECURSIVE NEURAL NETWORK (SIMPLE RNN) AND A RECURSIVE NEURAL NETWORK BASED ON LONG-TERM SHORT-TERM MEMORY (LSTM)
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Annotation: This article compares the accuracy of forecasting the value of a company's shares using a convolution neural network (CNN), a simple recursive neural network (SIMPLE RNN) and a long term memory based recursive neural network (LSTM).
Keywords: forecast, convolution neural network (CNN), simple recursive neural network (SIMPLE RNN), long term memory based recursive neural network (LSTM)
For citation: Kachalov O.I., Mironov A.N., Volodina A.M. Comparison of the accuracy of forecasting the value of the company's shares using a convolution neural network (cnn), a simple recursive neural network (simple rnn) and a recursive neural network based on long-term short-term memory (lstm) // Electronic Scientific Journal IT-Standard. – 2018. – No. 4. – pp. .