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Leveraging LSTM for Precision Inventory Management by Future Demand Forecasting

A deep-learning approach combining LSTM networks with customer purchase-pattern mining to forecast future demand and manage inventory, achieving 98 percent accuracy in the reported tests.

Editorial artwork standing in for this publication; no official cover exists for a journal article.

At a glance

Type

Journal article

Publisher

Journal of Applied Research and Technology

Year

2025

Also credited

With Aviral Kumar Tiwari and Rekh Ram Janghel

Read the article

"Leveraging LSTM for Precision Inventory Management by Future Demand Forecasting" appears in the Journal of Applied Research and Technology (Vol. 23, No. 1, pp. 8-21, 2025), co-authored by Aviral Kumar Tiwari, Jayarethanam Pillai and Rekh Ram Janghel, proposing an LSTM-based approach to identify high-utility items from customer buying patterns and manage inventory against future demand.

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