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Ushbu maqolada hozirgi davrda tobora raqamli texnologiyalarning yildan-yilga rivojlanib borishi asnosida sun’iy intellekt asosida ishlaydigan dasturlardan geografik axborot tizimlari (GAT) da foydalanish jihatlari haqida so‘z boradi.

  • Read count 49
  • Date of publication 05-07-2024
  • Main LanguageO'zbek
  • Pages406-414
Ўзбек

Ushbu maqolada hozirgi davrda tobora raqamli texnologiyalarning yildan-yilga rivojlanib borishi asnosida sun’iy intellekt asosida ishlaydigan dasturlardan geografik axborot tizimlari (GAT) da foydalanish jihatlari haqida so‘z boradi.

Русский

В данной статье говорится об аспектах использования программ искусственного интеллекта в географических информационных системах (ГИС) в условиях развития цифровых технологий из года в год.

English

This article talks about the aspects of using artificial intelligence programs in geographic information systems (GIS) in the context of the development of digital technologies from year to year

Author name position Name of organisation
1 Mirislomov M.. talabasi Chirchiq davlat pedagogika universiteti
Name of reference
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4 M. H. Hassoun, Fundamentals of Artificial Neural Network. Cambridge, Massachusetts Institute of Technology (MIT) Press, 1995
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8 Openshaw S, Openshaw C (1997) Artificial intelligence in geography. Wiley, New York
9 Stock K, Jones CB, Russell S, Radke M, Das P, Aflaki N (2022) Detecting geospatial location descriptions in natural language text. Int J Geogr Inf Sci 36(3):547– 584
10 Purves RS, Clough P, Jones CB, Hall MH, Murdock V et al (2018) Geographic information retrieval: progress and challenges in spatial search of text. Found Trends® Inf Retr 12(2–3):164–318
11 Mirislomov Mirdavlat GEOGRAFIK AXBOROT TIZIMI VA GEOGRAFIK TADQIQOTLARDA SUN’IY INTELLEKTGA ASOSLANGAN EKSPERT TIZIMLARINING O‘RNI VA AHAMIYATI // Raqamli iqtisodiyot (Цифровая экономика). 2024. №6. URL: https://cyberleninka.ru/article/n/geografikaxborot- tizimi-va-geografik-tadqiqotlarda-sun-iy-intellektga-asoslangan-eksperttizimlarining- o-rni-va-ahamiyati
12 Li, W., Zhou, B., Hsu, C.-Y., Li, Y. and Ren, F., Recognizing terrain features on terrestrial surface using a deep learning model: an example with crater detection. ed. Proceedings of the 1st Workshop on Artificial Intelligence and Deep Learning for Geographic Knowledge Discovery, 2017b, 33-36.
13 Li, W. and Hsu, C.-Y. 2018. Automated terrain feature identification from remote sensing imagery: a deep learning approach. International Journal of Geographical Information Science, 1-24.
14 Hu, Y., Li, W., Wright, D., Aydin, O., Wilson, D., Maher, O, and Raad, M. (2019). Artificial Intelligence Approaches. The Geographic Information Science & Technology Body of Knowledge (3rd Quarter 2019 Edition), John P. Wilson (ed.). DOI: https://doi.org/10.22224/gistbok/2019.3.4
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