Application of artifical intelligence and machine learning methods in rf-emf monitoring: an analytical review

Allamuratova , Zamira, Sarikulova , Fatima, Tajibaev , Nursultan

Techscience.uz - техника фанлари долзарб масалалри · 2026-yil

Annotatsiya

The article analyzes the application of artificial intelligence and machine learning methods for radiofrequency electromagnetic field monitoring. Existing approaches are compared, and a methodological approach is proposed to relate electromagnetic field prediction results to safety criteria and enable the early identification of potentially hazardous zones.

Maqola ma’lumotlari
MualliflarAllamuratova , Zamira, Sarikulova , Fatima, Tajibaev , Nursultan
JurnalTechscience.uz - техника фанлари долзарб масалалри
NashriyotЖиззах политехника институти
ISSN3030-3702, 3030-3702
Nashr sanasi2026-10-13
Jild4
Betlar4-17
TilIngliz
Ilmiy sohaTexnika
DOI10.47390/ts-v4is/5y2026n01
Indeksga qo‘shilgan2026-10-20

DOI: 10.47390/ts-v4is/5y2026n01 · Maqolaning asl sahifasi

Kalit so‘zlar

electromagnetic field, RF-EMF, electromagnetic safety, monitoring, artificial intelligence, artificial neural network, forecasting, hazardous zones., elektromagnit maydon, RF-EMF, elektromagnit xavfsizlik, monitoring, sun’iy intellekt, sun’iy neyron tarmog‘i, bashoratlash, xavfli zonalar.

Ilmiy soha

Texnika

Iqtibos keltirish

APAAllamuratova , Zamira, Sarikulova , Fatima, & Tajibaev , Nursultan (2026). APPLICATION OF ARTIFICAL INTELLIGENCE AND MACHINE LEARNING METHODS IN RF-EMF MONITORING: AN ANALYTICAL REVIEW. Techscience.uz - техника фанлари долзарб масалалри, 4, 4-17. https://doi.org/10.47390/ts-v4is/5y2026n01
GOST (OAK)Allamuratova , Zamira, Sarikulova , Fatima, Tajibaev , Nursultan APPLICATION OF ARTIFICAL INTELLIGENCE AND MACHINE LEARNING METHODS IN RF-EMF MONITORING: AN ANALYTICAL REVIEW // Techscience.uz - техника фанлари долзарб масалалри. – 2026. – T. 4. – P. 4-17. – DOI: 10.47390/ts-v4is/5y2026n01.
MLAAllamuratova , Zamira, Sarikulova , Fatima, and Tajibaev , Nursultan. “APPLICATION OF ARTIFICAL INTELLIGENCE AND MACHINE LEARNING METHODS IN RF-EMF MONITORING: AN ANALYTICAL REVIEW.” Techscience.uz - техника фанлари долзарб масалалри, 4, 4-17, 2026. https://doi.org/10.47390/ts-v4is/5y2026n01
ChicagoAllamuratova , Zamira, Sarikulova , Fatima, and Tajibaev , Nursultan. “APPLICATION OF ARTIFICAL INTELLIGENCE AND MACHINE LEARNING METHODS IN RF-EMF MONITORING: AN ANALYTICAL REVIEW.” Techscience.uz - техника фанлари долзарб масалалри, 4, 4-17 (2026). https://doi.org/10.47390/ts-v4is/5y2026n01
HarvardAllamuratova , Zamira, Sarikulova , Fatima, and Tajibaev , Nursultan (2026) ‘APPLICATION OF ARTIFICAL INTELLIGENCE AND MACHINE LEARNING METHODS IN RF-EMF MONITORING: AN ANALYTICAL REVIEW’, Techscience.uz - техника фанлари долзарб масалалри, 4, 4-17. https://doi.org/10.47390/ts-v4is/5y2026n01
BibTeX
@article{allamuratovazamira2026,
  title = {APPLICATION OF ARTIFICAL INTELLIGENCE AND MACHINE LEARNING METHODS IN RF-EMF MONITORING: AN ANALYTICAL REVIEW},
  author = {Allamuratova , Zamira and Sarikulova , Fatima and Tajibaev , Nursultan},
  journal = {Techscience.uz - техника фанлари долзарб масалалри},
  year = {2026},
  volume = {4},
  pages = {4-17},
  doi = {10.47390/ts-v4is/5y2026n01},
  url = {https://doi.org/10.47390/ts-v4is/5y2026n01}
}

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