MUMBAI, India, Aug. 10 -- Intellectual Property India has published a patent application (202641091336 A) filed by Bgs College Of Engineering And Technology Bgscet on July 28, 2026, for Deep Learning-Based Stock Market Prediction Method And System.
Inventors include Ravikumar Guralamata Krishnegowda; Govindaiah Thimma Raju; Jalaja Govindappa; Vedik Sunil Kumar; Vihas Yatheesh Halkurike; Manusha Poluru Yerriswamy; and Mouna Krishnegowda.
The application for the patent was published on July 31, 2026, under issue no. 31/2026.
Abstract: Reliable stock price prediction is challenging due to heterogeneous financial data, nonlinear market behaviour, and evolving market conditions. The present disclosure provides a computer-implemented method (300) and a deep learning-based stock market prediction system (210) configured to improve stock price prediction. The system comprises a data acquisition module (211) configured to acquire financial information from multiple independent data sources, a data preprocessing module (212) configured to validate, synchronise, clean, engineer features, and generate prediction-ready datasets, a prediction engine (213) configured to process sequential datasets using deep learning models to generate predicted stock prices, a model training and evaluation module (214) configured to optimise prediction performance, a results and visualization module (215) configured to generate analytical outputs, and a historical data repository (230) configured to support continuous model refinement using newly acquired financial information.
Disclaimer: Curated by HT Syndication.
