ATMOSFERA IFLOSLANISHINI 3D MODELLASHTIRISH VA EKOLOGIK XAVF ZONALARINI BAHOLASH UCHUN GIBRID AI–ML MODELI
Abstract
Ushbu maqolada atmosfera ifloslanishini bashorat qilish va ekologik xavf zonalarini aniqlash maqsadida gibrid sun’iy intellekt (AI) va mashinali o‘qitish (ML) modellariga asoslangan 3D modellashtirish yondashuvi taklif qilinadi. Taklif etilgan tizim fizik modellashtirish (Navye–Stoks va advektsiya-diffuziya tenglamalari) va chuqur o‘rganish (CNN, LSTM) algoritmlarini birlashtirib, PM2.5, NO₂, CO, O₃ kabi ifloslovchi moddalarning tarqalishini bashorat qiladi. Shuningdek, model yordamida yuqori konsentratsiyali zonalar 3D formatda qayta tiklanadi va ekologik xavf xaritalari ishlab chiqiladi. Mahalliy sharoitlarga moslashtirilgan ushbu yondashuv orqali O‘zbekiston shaharlarida havo sifatini yaxshilash va sog‘liq xavfini kamaytirish imkoniyatlari kengaytiriladi.
References
Oʻzbekiston Respublikasi Prezidentining 30.10.2019 yildagi “2030-yilgacha boʻlgan davrda Oʻzbekiston Respublikasining Atrof muhitni muhofaza qilish konsepsiyasini tasdiqlash toʻgʻrisida”gi PF-5863-son farmoni. https://lex.uz/docs/-4574008
https://www.gov.uz/en/activity_page/environment
Oʻzbekiston Respublikasi Prezidentining 24.09.2024 yildagi “Chang boʻronlariga qarshi kurashish va atmosfera havosi sifatini yaxshilash boʻyicha birinchi navbatdagi chora-tadbirlar toʻgʻrisida”gi PQ-338-son qarori https://lex.uz/uz/docs/-7112414
Liability for air pollution during construction has been introduced https://gov.uz/en/eco/news/view/38798
Air Quality Assessment for Tashkent and the Roadmap for Air Quality Management Improvement in Uzbekistan https://www.worldbank.org/en/country/uzbekistan/publication/air-quality-assessment-for-tashkent
Deep learning for 3D reconstruction and trajectory prediction of dust and polluted aerosols in educational environments https://www.frontiersin.org/journals/environmental-science/articles/10.3389/fenvs.2025.1582806/full
Subramaniam, S., Raju, N., Ganesan, A., Rajavel, N., Chenniappan, M., Prakash, C., Pramanik, A., Basak, A. K., & Dixit, S. (2022). Artificial Intelligence Technologies for Forecasting Air Pollution and Human Health: A Narrative Review. Sustainability, 14(16), 9951. https://doi.org/10.3390/su14169951
Yasmin, F., Hassan, M.M., Hasan, M. et al. AQIPred: A Hybrid Model for High Precision Time Specific Forecasting of Air Quality Index with Cluster Analysis. Hum-Cent Intell Syst 3, 275–295 (2023). https://doi.org/10.1007/s44230-023-00039-x
Maryam Rahmani. Next-Generation Air Pollution Forecasting: Integrating AI, Spatiotemporal Dynamics, and Privacy-Ensuring Approaches for Urban Areas. Computer Science[cs]. Université de Lille, 2024. English. ⟨NNT : ⟩. ⟨tel-04851216⟩
Computer Modeling of Aerosol Emissions Spread in the Atmosphere Daler Sharipov, Sharofiddin Aynakulov and Otabek Khafizov. https://doi.org/10.1051/e3sconf/20199705023
Madiyarova, U.; Erkinov, J.; Rachid, B.M. Particulate Matter (PM2.5) Prediction in Tashkent Using Machine Learning, in Proceedings of the 7th International Electronic Conference on Atmospheric Sciences, 4–6 June 2025, MDPI: Basel, Switzerland.
Panda, Ashok & Pradhan, Sonali & Pati, Chinmayee & Rath, Naba & Baral, Deepak. (2025). AI-Based Predictive Modeling For Air Quality Assessment And Environmental Risk Forecasting In Urban Ecosystems. International Journal of Environmental Sciences. 11. 163-171. 10.64252/n5gynb06.
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Ushbu litsenziyaga muvofiq, siz:
Ulashish — materialni istalgan vosita yoki formatda nusxalash va qayta tarqatish
Moslashtiring - remiks qiling, o'zgartiring va materialga asoslang
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