Ijtimoiy tarmoq ma'lumotlarini konvolyutsion neyron tarmoq yordamida tahlil qilish

Haydarova O'g'iloy Mansurovna; R. Shukurova

Article · 2021

Ijtimoiy tarmoq ma'lumotlarini konvolyutsion neyron tarmoq yordamida tahlil qilish

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20.2002/rtt/2021/v8_i4/36652184Uzbek

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Authors

Haydarova O'g'iloy Mansurovnano linked profile
Ташкентский государственный технический университет имени Ислама Каримова
R. Shukurovano linked profile
Islom Karimov nomidagi Toshkent davlat texnika universiteti

Abstract

Ushbu maqolada «Ijtimoiy tarmoq ma'lumotlarini konvolyutsion neyron tarmoq yordamida tahlil qilish» mavzusi tahlil qilingan. Tadqiqot davomida 510 nafar respondent ishtirokida tajriba-sinov ishlari o'tkazildi. Natijalar konvolyutsion neyron tarmoq samaradorligini oshirishga xizmat qiladi.

Keywords

Bibliographic details

DRI: 20.2002/rtt/2021/v8_i4/36652184
Work type: Article
Journal: Raqamli texnologiyalar va ta'limISSN 2181-1091
Volume and issue: Vol. 8, No. 4
Pages: 1–5
Published: 1 October 2021
Language: Uzbek
Full text: Open on the publisher's page (opens in a new tab)
Passport mirror: synced 21/09/2026, 16:48, version 1

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References

Sources cited by this work and how they were matched to works in the registry.

15 entries9 matched0 under review6 external

1.
Kamolova G.S., Ergashev Z.I., Haydarova O'.M. Применение искусственного интллекта в малого бизнеса (на примере Бухары) 73 // TDTU: fan, ta'lim va innovatsiya. – 2021. – №1. – B. 22–29. https://nationaldri.uz/20.1006/tdtufti/2021/v11_i1/66084847
MatchedExact by DRI→ Применение искусственного интеллекта в малого бизнеса (на примере Бухары) 73
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Brown A., Novak P. (2016). Deep residual learning for image recognition. IEEE Access, 174, 117–968. https://doi.org/10.1109/ACCESS.2016.345403
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Mo'minova N.B., Xoliqov O.G'., Mirzayev U.A., va boshq. Bobur ijodida badiiy detalning badiiy alqini // Sharqshunoslik. – 2013. – №4. – B. 34–38. DOI: 10.52038/sharq.2013.6.4.5
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Qosimov O.R., Eshmatova S.A., Mamatova G.I. Tibbiy tasvirlarni tasodifiy o'rmon algoritmi yordamida tahlil qilish // TATU: fan, ta'lim va innovatsiya. – 2014. – №2. – B. 1–7. URL: https://nationaldri.uz/20.1003/tatufti/2014/v2_i2/96279722
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Xoliqov, G'. Z., Haydarova, D. L., Xamidov, J. I., et al. (2014). Оптимизация температурного режима насосной станции методом математического моделирования. FarPI ilmiy-texnika jurnali, 2(3), 1–5.
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Qosimov O.R., G'afurova S.Sh. Geoaxborot tizimi uchun konvolyutsion neyron tarmoq asosida trafikni prognozlash // TDTU: fan, ta'lim va innovatsiya. – 2012. – №1. – B. 16–24. URL: https://nationaldri.uz/20.1006/tdtufti/2012/v2_i1/69024813
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Морозова Н.Г. Применение искусственного интеллекта в малого бизнеса // Химия и жизнь. – 2010. – № 2. – С. 62–114.
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Tanaka H., Martin C., Novak P. (2003). Thin film solar cells: materials and performance. IEEE Access, 80, 452–909. DOI: 10.1109/ACCESS.2003.801324
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Yoqubova X.S. Abdulla Oipov ijodida badiiy vaqt va makonning badiiy talqini // «Matematik fizika va tegishli muammolar» mavzusidagi xalqaro ilmiy-amaliy konferensiya materiallari. – Toshkent, 2014. – B. 1–3.
MatchedFuzzy match, S = 0.99
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Rustamova N.D. Ijtimoiy tarmoq maʻlumotlarini kriptografik protokollar yordamida tahlil qilish // «Tibbiyotning dolzarb muammolari» mavzusidagi xalqaro ilmiy-amaliy konferensiya materiallari. – Toshkent, 2017. – B. 21–23.
MatchedFuzzy match, S = 1.00
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Choriyeva M.H. Aqlli uy tizimi uchun chuqur o'rganish asosida nutqni tanib olish // Til va adabiyot ta'limi. – 2004. – №5. – B. 37–76.
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Jumayev U.N. Ta'lim sohasida sun'iy intellektni qo'llash. – Toshkent: Iqtisodiyot, 2019. – 141 b.
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Smirnov D.V. O'zbek tilidagi matnlar korpusi xavfsizligini ta'minlashda kompyuter ko'rishi imkoniyatlari. – Toshkent: Universitet, 2010. – 170 b.
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Mirzayeva, Z. K., Jo'rayeva, O. K., Eshmatov, S. D., et al. (2019). Issiqlik o'tkazuvchanlik tenglamasi uchun chegaraviy masalaning yechimi haqida (Surxondaryo viloyati misolida). O'zMU xabarlari, 7(3), 1–12. – DRI 20.1002/ozmux/2019/v7_i3/61222370
MatchedExact by DRI
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Kamolova G.S., Zokirov Sh.K. Application of clustering algorithms for detection // FarDU ilmiy xabarlar. – 2017. – №5. – B. 1–12.
MatchedFuzzy match, S = 1.00

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[1] 1.
Kamolova G.S., Ergashev Z.I., Haydarova O'.M. Применение искусственного интллекта в малого бизнеса (на примере Бухары) 73 // TDTU: fan, ta'lim va innovatsiya. – 2021. – №1. – B. 22–29. https://nationaldri.uz/20.1006/tdtufti/2021/v11_i1/66084847
MatchedExact by DRI→ Применение искусственного интеллекта в малого бизнеса (на примере Бухары) 73

[2] 2.
Brown A., Novak P. (2016). Deep residual learning for image recognition. IEEE Access, 174, 117–968. https://doi.org/10.1109/ACCESS.2016.345403
External source

[3] 3.
Mo'minova N.B., Xoliqov O.G'., Mirzayev U.A., va boshq. Bobur ijodida badiiy detalning badiiy alqini // Sharqshunoslik. – 2013. – №4. – B. 34–38. DOI: 10.52038/sharq.2013.6.4.5
MatchedExact by DOI

[4] 4.
Qosimov O.R., Eshmatova S.A., Mamatova G.I. Tibbiy tasvirlarni tasodifiy o'rmon algoritmi yordamida tahlil qilish // TATU: fan, ta'lim va innovatsiya. – 2014. – №2. – B. 1–7. URL: https://nationaldri.uz/20.1003/tatufti/2014/v2_i2/96279722
MatchedExact by DRI

[5] 5.
Xoliqov, G'. Z., Haydarova, D. L., Xamidov, J. I., et al. (2014). Оптимизация температурного режима насосной станции методом математического моделирования. FarPI ilmiy-texnika jurnali, 2(3), 1–5.
MatchedFuzzy match, S = 1.00

[6] 6.
Qosimov O.R., G'afurova S.Sh. Geoaxborot tizimi uchun konvolyutsion neyron tarmoq asosida trafikni prognozlash // TDTU: fan, ta'lim va innovatsiya. – 2012. – №1. – B. 16–24. URL: https://nationaldri.uz/20.1006/tdtufti/2012/v2_i1/69024813
MatchedExact by DRI

[7] 7.
Морозова Н.Г. Применение искусственного интеллекта в малого бизнеса // Химия и жизнь. – 2010. – № 2. – С. 62–114.
External source

[8] 8.
Tanaka H., Martin C., Novak P. (2003). Thin film solar cells: materials and performance. IEEE Access, 80, 452–909. DOI: 10.1109/ACCESS.2003.801324
External source

[9] 9.
Yoqubova X.S. Abdulla Oipov ijodida badiiy vaqt va makonning badiiy talqini // «Matematik fizika va tegishli muammolar» mavzusidagi xalqaro ilmiy-amaliy konferensiya materiallari. – Toshkent, 2014. – B. 1–3.
MatchedFuzzy match, S = 0.99

[10] 10.
Rustamova N.D. Ijtimoiy tarmoq maʻlumotlarini kriptografik protokollar yordamida tahlil qilish // «Tibbiyotning dolzarb muammolari» mavzusidagi xalqaro ilmiy-amaliy konferensiya materiallari. – Toshkent, 2017. – B. 21–23.
MatchedFuzzy match, S = 1.00

[11] 11.
Choriyeva M.H. Aqlli uy tizimi uchun chuqur o'rganish asosida nutqni tanib olish // Til va adabiyot ta'limi. – 2004. – №5. – B. 37–76.
External source

[12] 12.
Jumayev U.N. Ta'lim sohasida sun'iy intellektni qo'llash. – Toshkent: Iqtisodiyot, 2019. – 141 b.
External source

[13] 13.
Smirnov D.V. O'zbek tilidagi matnlar korpusi xavfsizligini ta'minlashda kompyuter ko'rishi imkoniyatlari. – Toshkent: Universitet, 2010. – 170 b.
External source

[14] 14.
Mirzayeva, Z. K., Jo'rayeva, O. K., Eshmatov, S. D., et al. (2019). Issiqlik o'tkazuvchanlik tenglamasi uchun chegaraviy masalaning yechimi haqida (Surxondaryo viloyati misolida). O'zMU xabarlari, 7(3), 1–12. – DRI 20.1002/ozmux/2019/v7_i3/61222370
MatchedExact by DRI

[15] 15.
Kamolova G.S., Zokirov Sh.K. Application of clustering algorithms for detection // FarDU ilmiy xabarlar. – 2017. – №5. – B. 1–12.
MatchedFuzzy match, S = 1.00

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