Intellectual Property India Publishes Patent Application for 'Demand Forecasting Of Products Using Deep Learning (LSTM)' Filed by Kg Reddy College Of Engineering and Technology

MUMBAI, India, Jan. 2 -- Intellectual Property India has published a patent application (202541122281 A) filed by Kg Reddy College Of Engineering and Technology, Hyderabad, Telangana, on Dec. 5, 2025, for 'demand forecasting of products using deep learning (lstm).'

Inventor(s) include Dr. Jhade Srinivas; Mrs. D. Prasanthi; Mr. Amaresh Kori; Mr. Mangalagiri Laxmikanth; Mr. Govardhan Logabiraman; Mr. Bande Ganesh; Mrs. S. Vijaya Bhargavi; Mrs. K. Gomathi; Mr. Shaik Mohd Adeib Arief; and Ms. Tahura Siddiqua.

The application for the patent was published on Jan. 2, under issue no. 01/2026.

According to the abstract released by the Intellectual Property India: "Demand forecasting of products using deep learning (LSTM) is the proposed invention. The urgency of addressing stock market volatility is underscored by the fact that accurate price prediction is critical for informed financial decision-making and risk management. Stock price forecasting remains a challenging task due to the inherently complex and dynamic nature of financial markets. Disparities in predictive accuracy arise from factors such as data quality, model selection, and feature engineering, significantly impacting the reliability of forecasts. This study leverages a Long Short-Term Memory (LSTM) network to enhance predictive performance in stock price forecasting by capturing temporal dependencies in historical price data. By integrating key market indicators and employing a structured preprocessing pipeline, the model aims to improve forecasting accuracy and mitigate prediction errors."

Disclaimer: Curated by HT Syndication.