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Temir yo'llarda yuk tashish xizmatlarining samaradorligini oshirish maqsadida hujjat aylanishi jarayonlarini avtomatlashtirish va optimallashtirish zarurati tug'ilmoqda. Sun'iy intellekt va ma'lumotlarni tahlil qilish usullaridan foydalanib, ma'lumotlar oqimini optimallashtirishning imkoniyatlari tadqiq etiladi.

  • Internet havola
  • DOI
  • UzSCI tizimida yaratilgan sana 20-01-2025
  • O'qishlar soni 27
  • Nashr sanasi 28-12-2024
  • Asosiy tilO'zbek
  • Sahifalar89-91
Ўзбек

Temir yo'llarda yuk tashish xizmatlarining samaradorligini oshirish maqsadida hujjat aylanishi jarayonlarini avtomatlashtirish va optimallashtirish zarurati tug'ilmoqda. Sun'iy intellekt va ma'lumotlarni tahlil qilish usullaridan foydalanib, ma'lumotlar oqimini optimallashtirishning imkoniyatlari tadqiq etiladi.

English

To enhance the efficiency of freight transportation services on railways, there is a growing need to automate and optimize documentation circulation processes. This study investigates the possibilities of optimizing data flow by utilizing artificial intelligence and data analysis methods.

№ Muallifning F.I.Sh. Lavozimi Tashkilot nomi
1 Tukhtakhodjaev A.B. Head of the Department Тashkent State Transport University
№ Havola nomi
1 Abdullayev A. "Logistika tizimlarida ma'lumotlar oqimini boshqarish". Toshkent: Logistika nashriyoti, 2020.
2 Karimov B. "Sun'iy intellekt va uning transport sohasidagi qo'llanilishi". Transport va logistika jurnali, 2021, №3, 45-52-betlar.
3 Smith J. "Intelligent Approaches to Data Flow Optimization in Freight Transportation". International Journal of Logistics, 2019, Vol. 22, Issue 4, pp. 345-360.
4 Lee K., Park S. "Digital Transformation in Railway Freight Documentation". Journal of Transportation Technologies, 2020, Vol. 10, pp. 150-162.
5 O'zbekiston Respublikasi Transport vazirligi rasmiy sayti: www.mintrans.uz
6 Chen Y. "Application of Machine Learning in Logistics Data Management". Logistics Research, 2018, Vol. 11, Issue 2, pp. 89-101.
7 Ivanov D. "Big Data Analytics in Railway Freight Transportation". Procedia Computer Science, 2019, Vol. 159, pp. 1086-1095.
8 Wang L., Zhang X. "Optimizing Data Flow in Supply Chain Management Using AI Techniques". International Journal of Supply Chain Management, 2021, Vol. 6, Issue 3, pp. 23-35.
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