Enhancing location accuracy in urban logistics using hybrid machine learning and deep learning models on large-scale global positioning system data

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Erdem E., Aydın T., Erkayman B.

CONNECTION SCIENCE, vol.38, no.1, pp.1-44, 2026 (SCI-Expanded, Scopus)

• Publication Type: Article / Article
• Volume: 38 Issue: 1
• Publication Date: 2026
• Doi Number: 10.1080/09540091.2026.2710512
• Journal Name: CONNECTION SCIENCE
• Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus, Aerospace Database, Applied Science & Technology Source, Compendex, INSPEC, Psycinfo, Directory of Open Access Journals, Academic Search Ultimate (EBSCO), Health Research Premium Collection (ProQuest), Psychology & Behavioral Sciences Collection (EBSCO), Technology Collection (ProQuest)
• Page Numbers: pp.1-44
• Keywords: GPS data analysis, urban logistics, location accuracy, ensemble models, deep learning models
• Ataturk University Affiliated: Yes