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Annotatsiya. Mazkur maqolada aloqa tarmoqlarida trafikni boshqarish masalasini hal etish uchun ko‘p mezonli optimallashtirishga asoslangan matematik model ishlab chiqilgan. Model tarmoq grafigi asosida tuzilgan bo‘lib, xizmat sifati ko‘rsatkichlari sifatida kechikish, o‘tkazuvchanlik va ishonchlilik alohida mezonlar tarzida hisobga olingan. Sun’iy intellekt yondashuvlari, jumladan kuchaytiruvchi o‘rganish va graf neyron tarmoqlari yordamida marshrutlarni moslashuvchan boshqarish imkoniyati nazarda tutilgan. Model Python muhiti asosida simulyatsiya qilinib, oddiy va nosozlik ssenariylari bo‘yicha sinovdan o‘tkazildi. Pareto-optimal yondashuv orqali murakkab tarmoq sharoitlarida qaror qabul qilishning samarali algoritmi ishlab chiqildi. Evolyutsion hisoblash usullari, xususan genetik algoritm va kuchaytiruvchi o‘rganish agentlari yordamida simulyatsiya o‘tkazilib, modelning barqarorligi va moslanuvchanligi eksperiment orqali asoslandi. Natijalar modelning barqaror ishlashi va topologiyadagi o‘zgarishlarga nisbatan yuqori moslanuvchanlikka ega ekanligini ko‘rsatdi.

  • Web Address
  • DOI
  • Date of creation in the UzSCI system 14-11-2025
  • Read count 63
  • Date of publication 13-11-2025
  • Main LanguageO'zbek
  • Pages116-121
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Annotatsiya. Mazkur maqolada aloqa tarmoqlarida trafikni boshqarish masalasini hal etish uchun ko‘p mezonli optimallashtirishga asoslangan matematik model ishlab chiqilgan. Model tarmoq grafigi asosida tuzilgan bo‘lib, xizmat sifati ko‘rsatkichlari sifatida kechikish, o‘tkazuvchanlik va ishonchlilik alohida mezonlar tarzida hisobga olingan. Sun’iy intellekt yondashuvlari, jumladan kuchaytiruvchi o‘rganish va graf neyron tarmoqlari yordamida marshrutlarni moslashuvchan boshqarish imkoniyati nazarda tutilgan. Model Python muhiti asosida simulyatsiya qilinib, oddiy va nosozlik ssenariylari bo‘yicha sinovdan o‘tkazildi. Pareto-optimal yondashuv orqali murakkab tarmoq sharoitlarida qaror qabul qilishning samarali algoritmi ishlab chiqildi. Evolyutsion hisoblash usullari, xususan genetik algoritm va kuchaytiruvchi o‘rganish agentlari yordamida simulyatsiya o‘tkazilib, modelning barqarorligi va moslanuvchanligi eksperiment orqali asoslandi. Natijalar modelning barqaror ishlashi va topologiyadagi o‘zgarishlarga nisbatan yuqori moslanuvchanlikka ega ekanligini ko‘rsatdi.

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