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동의어 포함
Purpose: This study aimed to develop a tailored Quality of Service (QoS) evaluation and prediction model specifically for mobility services using micro electric vehicles (MEVs). The purpose of this work was to enhance prediction accuracy and provide a more refined evaluation metric by analyzing user experience data, considering unique characteristics of MEVs.
Methods: A weighted evaluation model was developed to capture the interactions and significance of variables derived from user experience. Specifically, this study proposed a weighting method based on usage records, user driving patterns, and travel distances. A weighted regression analysis was then performed to objectively evaluate QoS, aiming to improve predictive power and interpretability.
Results: The findings highlighted that user experience history significantly influenced QoS, demonstrating the importance of tailored assessments for MEV-based mobility services using empirical data. The proposed weighted model has an advantage over traditional models in terms of prediction accuracy and interpretability.
Conclusion: To ensure the sustainability of MEV-based mobility services, it is essential to move beyond conventional survey-based QoS evaluations. Data-driven models incorporating user-specific factors provide more accurate and comprehensive assessment results. The application of the proposed model to real-world operational data demonstrated its effectiveness in improving the precision of QoS evaluations.*표시는 필수 입력사항입니다.
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도서위치안내: 정기간행물실(524호) / 서가번호: 국내11
2021년 이전 정기간행물은 온라인 신청(원문 구축 자료는 원문 이용)
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