Modelo Geoespacial-Matemático Integrado para el Desarrollo Económico Regional Mediante Inteligencia Artificial y Energía Sostenible
Resumen
El desarrollo económico regional en territorios rurales enfrenta desigualdades socioeconómicas, limitaciones energéticas y brechas tecnológicas que afectan la sostenibilidad productiva. Este estudio analiza modelos de gestión adaptativos que integran Inteligencia Artificial, sostenibilidad energética, gobernanza territorial e innovación social en comunidades rurales de Oaxaca, México. Se empleó un diseño metodológico mixto secuencial en cuatro fases: diagnóstico territorial inteligente, modelación predictiva, diseño adaptativo y validación participativa. El diagnóstico, basado en Sistemas de Información Geográfica, integró radiación solar estacional, infraestructura y acceso eléctrico, identificando patrones de vulnerabilidad y potencial energético. La modelación incorporó algoritmos de aprendizaje automático (Random Forest y XGBoost) y técnicas de Procesamiento de Lenguaje Natural para integrar variables territoriales y percepciones comunitarias. Los resultados demuestran que la convergencia entre Inteligencia Artificial, análisis geoespacial y participación social permite simular escenarios de desarrollo, optimizar intervenciones energéticas y fortalecer la gobernanza colaborativa, destacando el potencial de la energía solar como motor de economías locales sostenibles y resilientes.
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Derechos de autor 2026 Fabiola Colmenero Fonseca , Javier Cárcel-Carrasco, Juan Francisco Palomino Bernal
Esta obra está bajo licencia internacional Creative Commons Reconocimiento 4.0.
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