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@article{195382,
        author = {R.SUDHARSANA and A.S.THARVESH FATHIMA and K.SOWMIYA and E.GOMA},
        title = {POLISIM – AI-DRIVEN PUBLIC POLICY SIMULATION & IMPACT PREDICTION ENGINE},
        journal = {International Journal of Innovative Research in Technology},
        year = {2026},
        volume = {12},
        number = {11},
        pages = {32-38},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=195382},
        abstract = {POLISIM is a web-based Public Policy Simulation and Impact Prediction system designed to help organizations make smarter, data-driven decisions. Instead of relying on assumptions, the platform allows users to test policies and evaluate outcomes before implementation. Built with modern web technologies, it offers a smooth and responsive experience with secure data handling. The system provides role-based dashboards for administrators and decision-makers, enabling them to input policy details such as budget or operational changes and instantly view predicted results through simple visualizations. It also supports “what-if” analysis, helping users compare different strategies and understand their impact on performance and cost. Key features include real-time analytics, secure access, and automated reports. With its scalable and user-friendly design, POLISIM reduces uncertainty, improves transparency, and supports faster, more confident decision-making.},
        keywords = {POLISIM, Policy Simulation, Predictive Analytics, Decision Support System, Machine Learning},
        month = {March},
        }