IOT SENSORLARIDAN OLINGAN MA’LUMOTLAR ARXITEKTURASI VA ISHLOV BERISH USULLARI VA ALGORITMLARI

Mualliflar

  • Otabek Xo'jayev
  • Zilola Ro‘zmetova

Kalit so'zlar

https://doi.org/10.47390/ts-v3i8y2025No1

Kalit so'zlar

IoT sensorlari, ma’lumotlar arxitekturasi, intellektual tahlil, mashinaviy o‘qitish, chuqur o‘rganish, bashorat modellari, algoritmik samaradorlik, sun’iy intellekt

Annotasiya

Ushbu maqolada IoT sensorlaridan olingan ma’lumotlarning arxitekturasi, ularni qayta ishlash bosqichlari hamda algoritmik yondashuvlar asosida intellektual tahlil qilish imkoniyatlari keng yoritiladi. Ma’lumotlarni yig‘ish, uzatish, saqlash, tozalash va normallashtirish jarayonlari, shuningdek, real vaqt rejimida bashoratlash tizimlari tahlil qilinadi. Sun’iy intellekt va mashinaviy o‘qitish usullari bilan uyg‘unlashtirilgan arxitektura samaradorlikni oshirish hamda IoT tizimlarining barqarorligini ta’minlashda muhim ilmiy-amaliy yechim sifatida baholanadi

Manbalar

1. LeCun, Y., Bengio, Y., & Hinton, G. (2015). “Deep learning”. Nature, 521(7553), 436–444. [ https://doi.org/10.1038/nature14539 ] (https://doi.org/10.1038/nature14539 )

2. Schmidhuber, J. (2015). “Deep learning in neural networks: An overview”. Neural Networks, 61, 85–117. [ https://doi.org/10.1016/j.neunet.2014.09.003 ] (https://doi.org/10.1016/j.neunet.2014.09.003)

3. Zhang, Z., & Yang, J. (2021). “IoT data analytics for predictive maintenance using deep learning models”. IEEE Internet of Things Journal, 8(5), 3452–3463. [https://doi.org/10.1109/JIOT.2020.3021234](https://doi.org/10.1109/JIOT.2020.3021234 )

4. Xo‘jayev, O. K. (2021). “Sun’iy intellekt asosida ma’lumotlarni tahlil qilish usullari”. Tashkent: Fan va texnologiya nashriyoti.

5. Karimov, B. (2022). “IoT ma’lumotlarini intellektual qayta ishlash algoritmlarining samaradorligi”. “Axborot texnologiyalari va innovatsion tadqiqotlar” jurnali, 4(2), 57–64.

6. Ruzmetova, Z. (2023). “Ma’lumotlarni chuqur o‘rganish asosida IoT tarmoqlarida bashorat modellarini shakllantirish”. “Kompyuter tizimlari va tarmoqlar” ilmiy jurnali, 5(1), 88–96.

7. Goodfellow, I., Bengio, Y., & Courville, A. (2016). “Deep Learning”. MIT Press.”

8. Hassan, M. M., Gumaei, A., Alrubaian, M., & Fortino, G. (2019). “A hybrid deep learning model for efficient intrusion detection in big data environment”. Information Sciences, 513, 386–396. [ https://doi.org/10.1016/j.ins.2019.10.010 ]

( https://doi.org/10.1016/j.ins.2019.10.010 )

9. Ergashev, I., & Nurmatov, A. (2020). “IoT tizimlarida ma’lumotlarni boshqarish va xavfsizlik muammolari”. “Informatika va axborot texnologiyalari” jurnali, 3(2), 45–52.

10. Jalolov, M. (2022). *Mashinali o‘qitish algoritmlarining tibbiyotdagi qo‘llanishi*. “Sun’iy intellekt va zamonaviy axborot texnologiyalari” jurnali, 6(1), 101–110.

11. Shalev-Shwartz, 2014.

12. Bishop C.M. Pattern Recognition and Machine Learning (2006).pdf.

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Yuborilgan

2025-10-11

Nashr qilingan

2025-10-11

Qanday ko'rsatish

Xo'jayev , O., & Ro‘zmetova , Z. (2025). IOT SENSORLARIDAN OLINGAN MA’LUMOTLAR ARXITEKTURASI VA ISHLOV BERISH USULLARI VA ALGORITMLARI. Techscience Uz - Topical Issues of Technical Sciences, 3(8), 4–8. https://doi.org/10.47390/ts-v3i8y2025No1

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