Patrones de Comportamiento en usuarios de transporte interprovincial en Ecuador mediante Técnicas de Machine Learning

• Gabriela del Cisne Solano Aguilar https://orcid.org/0009-0007-7565-4702
• José Fernando López Aguirre https://orcid.org/0000-0001-9706-5115
• Juan Carlos Pomaquero Yuquilema https://orcid.org/0000-0003-0952-943X
• María Gabriela Tobar Ruiz https://orcid.org/0000-0002-3796-0545

Abstract

Este estudio tiene como objetivo analizar y predecir patrones de comportamiento de los usuarios de transporte interprovincial en Ecuador mediante técnicas de aprendizaje automático. Se utilizó un conjunto de datos proporcionado por la Unión de Cooperativas de Transporte Interprovincial de Ecuador que abarca viajes realizados entre 2022 y 2024. La metodología incluyó la implementación de K-means para la segmentación de usuarios y PCA para la reducción dimensional. Inicialmente, K-means identificó cuatro clústeres, pero el solapamiento entre grupos motivó la aplicación de PCA, mejorando la separación. Los resultados revelaron cuatro grupos: Ritmo Diario, Exploradores de Fin de Semana, Nómadas de Eventos y Viajeros Flexibles. Esta segmentación ofrece información clave para optimizar los servicios de transporte y mejorar la experiencia del usuario al ajustar recursos a las necesidades de cada grupo.

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