Sales Forecasting using RNN

In today’s world, big malls and marts are in need of advanced prediction of sales forecasting for the future demand of the products. This leads the manufacturer to produce sufficient product without excess production and to avoid such loss, we need to predict the future demand of a product using Rec...

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Bibliographic Details
Published in:International journal of innovative technology and exploring engineering 2019-07, Vol.8 (9), p.2748-2751
Main Authors: T R, Kalaiarasan, V, Dr Anandkumar, A M, Ratheeshkumar
Format: Article
Language:English
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Summary:In today’s world, big malls and marts are in need of advanced prediction of sales forecasting for the future demand of the products. This leads the manufacturer to produce sufficient product without excess production and to avoid such loss, we need to predict the future demand of a product using Recurrent Neural Network. Long Short Term Memory (LSTM) model deals with the most important past behaviors and understands whether or not those behaviors are important features in making future predictions. Thus, we can reduce the wastage of the product and an increase in profit. In addition, the sales team can communicate with the manufacturing unit in case of insufficient product. This leads to avoiding excess quantity preparation from the production unit. Sales prediction and forecasting is always a best practice for company development.
ISSN:2278-3075
2278-3075
DOI:10.35940/ijitee.I8428.078919