ANFIS YORDAMIDA EKINLARNI AVTOMATIK SUG‘ORISH TIZIMLARI: KONSEPTUAL YONDASHUV VA AMALIYOT

Ollabergan Yuldashov

Vol. 2 No. 11 (2024), Articles

Vol. 2 No. 11 (2024)

ANFIS YORDAMIDA EKINLARNI AVTOMATIK SUG‘ORISH TIZIMLARI: KONSEPTUAL YONDASHUV VA AMALIYOT

Articles

Published 2024-12-10

Ollabergan Yuldashov ⁺⁻

Ollabergan Yuldashov

Urganch davlat universiteti o‘qituvchisi

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Keywords

ANFIS
fuzzy
neyron tarmoq
chiziqli regressiya
avtomatik sug‘orish tizimi.

How to Cite

ANFIS YORDAMIDA EKINLARNI AVTOMATIK SUG‘ORISH TIZIMLARI: KONSEPTUAL YONDASHUV VA AMALIYOT. (2024). Journal of Science-Innovative Research in Uzbekistan, 2(11), 521-525. https://universalpublishings.com/~niverta1/index.php/jsiru/article/view/8623

Abstract

Ekinlarni sug‘orish jarayoni zamonaviy qishloq xo‘jaligida muhim rol o‘ynaydi, chunki suvni samarali boshqarish ekinlarning o‘sishi va mahsuldorligini ta’minlashga yordam beradi. Ushbu maqolada ANFIS (Adaptive Neuro-Fuzzy Inference System) yordamida ekinlarni avtomatik sug‘orish tizimi ishlab chiqildi. Tizim harorat va namlikni hisobga olgan holda ekinlarni sug‘orish rejimini boshqaradi. Fuzzy mantiq va chiziqli regressiya usullari yordamida, harorat va namlikning turli darajalarida suv sarfi bashorat qilinadi. Maqolada, tizimning ishlash prinsipi, foydalanilgan metodologiyalar va python dasturlash tilida yaratilgan loyiha tahlil qilinadi

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References

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2. Komilova Zulxumor Xokimovna, Rustamova Xusnida Orifjon qizi. (2024) “ANFIS arxitekturasi va qat'iy mas gibrid klassifikatorlar: sun'iy intellekt sohasidagi qo‘llanilislari va imkoniyatlari”, Pedagogik islohotlar va ularning yechimlari. 391-397.

3. Smith, H. & Lee, R. (2017). "Fuzzy Logic Applications in Agriculture," Agricultural Systems Journal, 45(3), 89-102.

4. Rajashekar, S., & Kumar, M. (2019). "Automated Irrigation Using ANFIS System," International Journal of Agriculture and Technology, 11(2), 112-120.

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6. https://github.com/OllaberganYuldashov/ANFIS

7. Chin, R. J., Lai, S. H., Ibrahim, S., Jaafar, W. Z. W., & Elshafie, A. (2019). ANFIS-based model for predicting actual shear rate associated with wall slip phenomenon. Soft Computing.