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Multisteps Sales Forecasting using LSTM Compared to GMDH

by Ghita Rguiga, Jamal Benhra
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 183 - Number 1
Year of Publication: 2021
Authors: Ghita Rguiga, Jamal Benhra
10.5120/ijca2021921283

Ghita Rguiga, Jamal Benhra . Multisteps Sales Forecasting using LSTM Compared to GMDH. International Journal of Computer Applications. 183, 1 ( May 2021), 46-50. DOI=10.5120/ijca2021921283

@article{ 10.5120/ijca2021921283,
author = { Ghita Rguiga, Jamal Benhra },
title = { Multisteps Sales Forecasting using LSTM Compared to GMDH },
journal = { International Journal of Computer Applications },
issue_date = { May 2021 },
volume = { 183 },
number = { 1 },
month = { May },
year = { 2021 },
issn = { 0975-8887 },
pages = { 46-50 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume183/number1/31895-2021921283/ },
doi = { 10.5120/ijca2021921283 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-07T01:15:37.833691+05:30
%A Ghita Rguiga
%A Jamal Benhra
%T Multisteps Sales Forecasting using LSTM Compared to GMDH
%J International Journal of Computer Applications
%@ 0975-8887
%V 183
%N 1
%P 46-50
%D 2021
%I Foundation of Computer Science (FCS), NY, USA
Abstract

This work reports the effectiveness of using Recurrent Neural Network LSTMs for multistep sales forecasting instead of a standalone approach and the use of time series data, treatment of inflation, forecasting options and tunings to help decision executives make better decisions on forecast and management systems. This work is lead on historical sales based on a year of demand records, the program established using LSTMs showed minimal loss and optimal forecasts compared to prediction using GMDH which is known for management forecasts such as inventories and sales forecasting.

References
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Index Terms

Computer Science
Information Sciences

Keywords

LSTM RNN GMDH Sales Forecasting Artificial Intelligence Supply Chain Management