Using LSTM, time series forecasting models can predict future values based on previous, sequential data . This provides greater accuracy for demand forecasters which results in better decision making for the business.
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– Compare the performance of LSTM and ARIMA with respect to minimization achieved in the error rates in prediction. The study shows that LSTM outperforms ARIMA . The average reduction in error rates obtained by LSTM is between 84 – 87 percent when compared to ARIMA indicating the superiority of LSTM.
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