MUMBAI, India, July 7 -- Intellectual Property India has published a patent application (202641076621 A) filed by Dr. K. V. Siva Prasad Reddy; G. Madhavi; Dr. Muntimadugu Vijaya Kanth; Dr U Rakesh; Ms. Chakala Navya; Dr. T. Charan Singh; Kommala Aparna; and Geetha Vadnala on June 20, 2026, for Time-Series Forecasting Analysis For Supply Chain Resilience And Hybrid Model Improvements.

Inventors include Dr. K. V. Siva Prasad Reddy; G. Madhavi; Dr. Muntimadugu Vijaya Kanth; Dr U Rakesh; Ms. Chakala Navya; Dr. T. Charan Singh; Kommala Aparna; and Geetha Vadnala.

The application for the patent was published on July 03, 2026, under issue no. 27/2026.

Abstract: This invention presents a novel Hybrid Time-Series Forecasting System for Supply Chain Resilience and Model Improvements that addresses critical limitations in traditional forecasting by dynamically fusing statistical foundations with advanced neural architectures and contextual external signals. The system is engineered to deliver accurate, probabilistic predictions of demand, inventory requirements, and potential disruptions in volatile supply chain ecosystems, thereby enabling proactive risk mitigation and operational optimization. Unlike conventional single-model approaches that struggle with nonlinearities, sudden shocks, or evolving patterns, this hybrid methodology decomposes time-series data into linear trend components handled by enhanced statistical models and residual nonlinearities captured through attention-augmented neural networks and ensemble boosting techniques. Key innovations include bidirectional feedback loops for continuous model refinement, integration of real-time multimodal inputs such as weather, geopolitical indicators, and market sentiment, and built-in resilience scoring that quantifies vulnerability to disruptions. Extensive validation on diverse datasets reveals substantial gains in forecast accuracy, reduced stockouts, lower holding costs, and faster adaptation to anomalies, positioning the invention as a scalable, privacy-preserving solution applicable across manufacturing, retail, logistics, and healthcare sectors. Overall, it advances supply chain intelligence by providing interpretable, adaptive forecasts that strengthen business continuity in uncertain global markets.

Disclaimer: Curated by HT Syndication.