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@article{204060,
        author = {Aman Kumar and Chiman Saini and Sangeeta Rani},
        title = {Autonomous Decision Intelligence with Generative Agentic AI for Climate Forecasting and Disaster Early Warning},
        journal = {International Journal of Innovative Research in Technology},
        year = {2026},
        volume = {13},
        number = {1},
        pages = {654-666},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=204060},
        abstract = {Climate change has made extreme weather events more common and more severe, so there are urgent needs for accurate climate forecasting and effective disaster early warning systems. Conventional forecasting systems frequently depend on non-adaptive analytical pipelines and human-in-the-loop decisions, introducing delays in response to fast-evolving disasters like these. We propose an innovative framework of autonomous decision intelligence based on generative agentic artificial intelligence (AI) for climate forecasting and disaster early warning. The framework proposed that integrates multi-parameter, climate data, generative AI models and autonomous reasoning agents with adaptive decision engines (READ) to improve forecasting accuracy, optimize warning lead times and direct rapid emergency response coordination. Tests on simulated cyclone, flood and wildfire datasets show that in comparison with conventional machine learning methods, improved prediction accuracy, response prioritization and warning dissemination efficiency are achieved. This study responses on practical viability of agentic AI in environmental intelligence systems by discussing interpretability, computational cost, ethics and governance, resilient infrastructure issues.},
        keywords = {Autonomous Decision Intelligence, Generative AI, Agentic AI, Climate Forecasting, Disaster Early Warning, Environmental Intelligence, Deep Learning.},
        month = {June},
        }