Quantum-Inspired Vulnerability Classifier for Socioeconomic Risk Assessment

AI-Powered Computational Tool for Multi-Dimensional Vulnerability Analysis This SKILL implements a quantum-inspired classification algorithm for assessing socioeconomic vulnerability across multiple dimensions including economic fragility, social exclusion, and institutional access barriers. Key Features: Quantum superposition-inspired feature weighting; probabilistic risk scoring; multi-criteria vulnerability indexing; automated classification into risk categories; interpretable decision pathways for policy intervention. Potential Applications: Can be integrated into social policy design systems, public resource allocation frameworks, early warning systems for poverty intervention, and academic research on inequality metrics. Supports real-time vulnerability monitoring and predictive modeling for social programs. Technical Specifications: Python-based implementation; modular architecture for custom feature engineering; extensible classification taxonomy; CSV/JSON data input/output; visualization-ready scoring outputs. Developed at UFMT (Universidade Federal de Mato Grosso). CAPES/CNPq PTT classification: SKILL (AI-powered computational tool). Part of this content may have been AI-generated under supervision by Daniel Maciel and Arturo Zavala.