Authors:
Maria Camila Reinoso Galvez, Paula Castellanos, Vinicius Souto
Graduate Certificate in Logistics and Supply Chain Management (GCLOG)
Summary:
This study presents a data-driven approach to forecast household solid waste generation in Quinta Normal by integrating municipal, demographic, climatic, and socioeconomic data. Preliminary Random Forest models capture spatial–temporal variability and seasonal patterns, demonstrating the potential of predictive analytics for municipal planning
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