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ISSN Approved Journal No: 2455-2631 | Impact factor: 8.15 | ESTD Year: 2016
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Issue: November 2022

Volume 7 | Issue 11

Impact factor: 8.15

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Paper Title: Application of Artificial neural networks in Time series forecasting
Authors Name: M. Narsimulu
Unique Id: IJSDR2211025
Published In: Volume 7 Issue 11, November-2022
Abstract: The most important lagged components in time series forecasting can be found using an advanced method introduced in this article called an artificial neural network model is Long Short-Term Memory (LSTM). Additionally, this article compares the forecasting accuracy of the traditional ARIMA model utilizing time series data with the artificial neural network model is LSTM. Collected rainfall data for India from 1901 to 2015. According to our findings, the coefficient of multiple determination (R2), mean absolute error (MAE), root mean squared error (RMSE), mean absolute percentage error (MAPE), the best predicting accuracy is offered by Long Short-Term Memory (LSTM) neural networks, which are more advanced than traditional time series approaches and the traditional ARIMA model.
Keywords: time series forecasting, artificial neural networks, ARIMA model, LSTM
Cite Article: "Application of Artificial neural networks in Time series forecasting", International Journal of Science & Engineering Development Research (www.ijsdr.org), ISSN:2455-2631, Vol.7, Issue 11, page no.154 - 158, November-2022, Available :http://www.ijsdr.org/papers/IJSDR2211025.pdf
Downloads: 000150694
Publication Details: Published Paper ID: IJSDR2211025
Registration ID:202466
Published In: Volume 7 Issue 11, November-2022
DOI (Digital Object Identifier):
Page No: 154 - 158
Publisher: IJSDR | www.ijsdr.org
ISSN Number: 2455-2631

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