MUMBAI, India, July 24 -- Intellectual Property India has published a patent application (202611065067 A) filed by Greater Noida Institute Of Technology Engineering Institute on May 23, 2026, for Hybrid Machine-Learning Climate Simulation System With Multi-Source Environmental Data Fusion And Predictive Scenario Modelling.
Inventors include Ms. Manisha; Rajeev Mishra; Vishwa Vijay Yadav; Prakhar Pandey; Smita Soni; Riyanshu Kumar; Abhay Vishwakarma; and Abhishek Yadav.
The application for the patent was published on July 17, 2026, under issue no. 29/2026.
Abstract: Abstract A hybrid machine-learning climate simulation system includes a data ingestion interface, processor, memory, preprocessing module, feature engineering module, hybrid model package, ensemble integration module, validation module, and predictive output interface. Historical and real-time climate data from weather stations, satellite sources, and climate repositories is cleaned, normalized, and selected to form predictor and target variables. Temporal, seasonal, and spatial features are generated from the selected variables. A hybrid model package combines statistical modelling, machine learning modelling, and deep learning modelling, including ARIMA, regression, Random Forest, Support Vector Machine, neural network, or LSTM-based processing. Outputs from the modelling units are integrated by weighted averaging or stacking to produce a trained climate model. Newly received climate variables are processed through the trained model to estimate target variables such as future temperature, precipitation, or other environmental indicators for climate scenario modelling. Dated 13 May 2026 Kumar Tushar Srivastava IN/PA- 3973 Agent for the Applicant
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