Leveraging deep learning models for optimized cargo tracking and transportation efficiency in Logistics

Nurullaev, Azam, Нуруллаев, Азам, Нуруллаев, Азам

Жамият ва инновациялар / Общество и инновации / Society and innovations · 2024-yil

Annotatsiya

Amid the digital transformation of the logistics industry, smart logistics algorithms have emerged as a crucial technology to enhance efficiency and reduce costs. This paper reviews the evolution of traditional logistics technologies and highlights the pivotal roles played by advancements such as the Internet of Things, big data analytics, artificial intelligence, and automation in driving logistics innovation. It delves into the application of intelligent logistics algorithms across areas like path optimization, intelligent scheduling, data mining and prediction, and smart warehousing. To address the challenge of inconsistencies between training and testing objectives, the paper introduces DRL4Route, a deep reinforcement learning-based framework for path optimization, along with the DRL4Route-GAE model. Extensive offline experiments and online deployments validate that the model significantly outperforms existing optimal benchmark methods on real datasets, improving metrics like location deviation squared and top-three location prediction accuracy. These research findings provide essential support for advancing the intelligent development of the logistics industry.

Maqola ma’lumotlari
MualliflarNurullaev, Azam, Нуруллаев, Азам, Нуруллаев, Азам
JurnalЖамият ва инновациялар / Общество и инновации / Society and innovations
NashriyotIn Science МЧЖ
ISSN2181-1415
Nashr sanasi2024-11-15
Jild5
Son6
Betlar181-192
TilIngliz
DOI10.47689/2181-1415-vol5-iss6-pp181-192
Indeksga qo‘shilgan2026-08-26

DOI: 10.47689/2181-1415-vol5-iss6-pp181-192 · Maqolaning asl sahifasi

Kalit so‘zlar

smart logistics algorithms, route optimization, advanced reinforcement learning, data analysis, enhancement of transportation efficiency, умные алгоритмы логистики, оптимизация маршрутов, продвинутое обучение с подкреплением, анализ данных, повышение эффективности транспортировки, ақлли логистика алгоритмлари, йўналишни оптималлаштириш, илғор мустаҳкамлашга асосланган ўрганиш, маълумотларни таҳлил қилиш, транспорт самарадорлигини ошириш

Iqtibos keltirish

APANurullaev, Azam, Нуруллаев, Азам, & Нуруллаев, Азам (2024). Leveraging deep learning models for optimized cargo tracking and transportation efficiency in Logistics. Жамият ва инновациялар / Общество и инновации / Society and innovations, 5(6), 181-192. https://doi.org/10.47689/2181-1415-vol5-iss6-pp181-192
GOST (OAK)Nurullaev, Azam, Нуруллаев, Азам, Нуруллаев, Азам Leveraging deep learning models for optimized cargo tracking and transportation efficiency in Logistics // Жамият ва инновациялар / Общество и инновации / Society and innovations. – 2024. – T. 5, № 6. – P. 181-192. – DOI: 10.47689/2181-1415-vol5-iss6-pp181-192.
MLANurullaev, Azam, Нуруллаев, Азам, and Нуруллаев, Азам. “Leveraging deep learning models for optimized cargo tracking and transportation efficiency in Logistics.” Жамият ва инновациялар / Общество и инновации / Society and innovations, 5(6), 181-192, 2024. https://doi.org/10.47689/2181-1415-vol5-iss6-pp181-192
ChicagoNurullaev, Azam, Нуруллаев, Азам, and Нуруллаев, Азам. “Leveraging deep learning models for optimized cargo tracking and transportation efficiency in Logistics.” Жамият ва инновациялар / Общество и инновации / Society and innovations, 5(6), 181-192 (2024). https://doi.org/10.47689/2181-1415-vol5-iss6-pp181-192
HarvardNurullaev, Azam, Нуруллаев, Азам, and Нуруллаев, Азам (2024) ‘Leveraging deep learning models for optimized cargo tracking and transportation efficiency in Logistics’, Жамият ва инновациялар / Общество и инновации / Society and innovations, 5(6), 181-192. https://doi.org/10.47689/2181-1415-vol5-iss6-pp181-192
BibTeX
@article{nurullaevazam2024,
  title = {Leveraging deep learning models for optimized cargo tracking and transportation efficiency in Logistics},
  author = {Nurullaev, Azam and Нуруллаев, Азам and Нуруллаев, Азам},
  journal = {Жамият ва инновациялар / Общество и инновации / Society and innovations},
  year = {2024},
  volume = {5},
  number = {6},
  pages = {181-192},
  doi = {10.47689/2181-1415-vol5-iss6-pp181-192},
  url = {https://doi.org/10.47689/2181-1415-vol5-iss6-pp181-192}
}

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