Psevdotasodifiy sonlar generatorini (PRNG) tekshirish va tahlil qilish
Keywords:
psevdotasodifiy sonlar generatori, PRNG, random modul, Python, ehtimollar nazariyasi, statistik tahlil, takrorlanish chastotasi, bir tekis taqsimot.Abstract
Ushbu maqolada psevdotasodifiy sonlar generatorining (PRNG) ishlash samaradorligi va statistik xususiyatlari tahlil qilindi. Tadqiqot davomida Python dasturlash tilining `random` moduli yordamida sonlar generatsiya qilindi. Olingan natijalar asosida sonlarning takrorlanish chastotasi, taqsimotning bir tekisligi hamda generatorning amaliy ishonchliligi baholandi. Tahlil natijalari PRNG tomonidan yaratilgan qiymatlar nazariy ehtimollik qonunlariga mos ravishda deyarli teng taqsimlanganini ko‘rsatdi. Tadqiqot psevdotasodifiy sonlar generatorlarining statistik modellashtirish va dasturiy simulyatsiyalarda samarali qo‘llanilishini tasdiqlaydi.
References
Anton Novikau, “Analysis of Pseudorandom Number Generator in Python”, International Journal of Science and Engineering Applications Volume 13-Issue 12, 01 – 04, 2024, ISSN:- 2319 - 7560 DOI: 10.7753/IJSEA1312.1001
Benjamin Antunes, David R.C Hill, “Reproducibility, energy efficiency and performance of pseudorandom number generators in machine learning: a comparative study of python, numpy, tensorflow, and pytorch implementations” , https://doi.org/10.48550/arXiv.2401.17345
ArjunBhamra, “Randomness and Pseudorandom Number Generators”, 2023
Michael Goodrich, “Generating Random and Pseudorandom Numbers”




