Оптимизация режимов работы насосной станции методом математического моделирования

O'g'iloy Haydarova

doi:10.52017/tdtufti.2015.5.1.2

Article · 2015

Оптимизация режимов работы насосной станции методом математического моделирования

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20.1006/tdtufti/2015/v5_i1/61514648Russian

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Authors

O'g'iloy Haydarova ORCID 0000-0002-0017-847X (opens in a new tab)
Islom Karimov nomidagi Toshkent davlat texnika universiteti

Abstract

В статье рассматриваются вопросы темы «Оптимизация режимов работы насосной станции методом математического моделирования». Проведён анализ отечественного и зарубежного опыта. Предложены практические рекомендации.

Keywords

Bibliographic details

DRI: 20.1006/tdtufti/2015/v5_i1/61514648
Work type: Article
Journal: TDTU: fan, ta'lim va innovatsiyaISSN 2181-0354
Volume and issue: Vol. 5, No. 1
Pages: 12–20
Published: 6 February 2015
Language: Russian
External DOI: 10.52017/tdtufti.2015.5.1.2 (opens in a new tab)
Full text: Open on the publisher's page (opens in a new tab)
Passport mirror: synced 21/09/2026, 16:47, version 1

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Citations

Excluding self-citations: 26

Excluding self-citations

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References

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

20 entries12 matched0 under review8 external

1.
Yusupova L.B., Zaripov A.Z., Ergashev H.I., va boshq. Geotermal energiya manbalaridan foydalanib tishli uzatma energiya samaradorligini oshirish // TDTU: fan, ta'lim va innovatsiya. – 2012. – №2. – B. 10–16. DRI: 20.1006/tdtufti/2012/v2_i2/51616884
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Shukurova R.N., Normatova U.M., Abdurahmonov S.J. Quyosh kollektori rejimini matematik modellashtirish yordamida optimallashtirish // TDTU: fan, ta'lim va innovatsiya. – 2012. – №2. – B. 1–9.
MatchedFuzzy match, S = 1.00→ Quyosh kollektori ish rejimini matematik modellashtirish yordamida optimallashtirish
3.
Chen Y., Wang L. (2011). Machine learning methods for credit scoring: evidence from panel data. IEEE Access, 39, 722–989. https://doi.org/10.1109/ACCESS.2011.626736
External source
4.
Po'latov, K. K. (2013). Оптимизация температурного режима солнечного коллектора емтодом математического моделирования. O'zMU xabarlari, 1–11. URL: https://nationaldri.uz/20.1002/71952824
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Fayziyeva S.Z., Xamidova U.F. Nasos stansiyasi mustahkamlik ko'rsatkichlarini imitatsion modellashtirish yordamida optimallashtirish. – Toshkent: Innovatsiya, 2013. – 301 b.
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Abdurahmonova, S. M., Nazarova, Z. I., Ibragimova, Z. A., et al. (2014). Issiqlik almashtirgich uchun nanomateriallar asosida konstruksiya ishlab chiqish. FarPI ilmiy-texnika jurnali, 2(1), 1–8.
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Umarov B.Z., Mamatova O.M. Paxta tozalash mashinasi harorat rejimini genetik algoritm yordamida optimallashtirish // O’zDJTU ilmiy-uslubiy jurnali. – 2012. – №4. – B. 22–29.
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Haydarova, O'. M., & Zaripov, A. Z. (2014). Quyosh kollektori uchun mahalliy xomashyo asosida yangi konstruksiya ishlab chiqish. Texnika yulduzlari, 1–4. https://doi.org/10.52015/ty.2014.4.12.1
MatchedExact by DOI
9.
Umarov, B. Z., Moʼminova, Z. V., & Zaripova, Oʼ. A. (2013). Tishli uzatma uchun polimer qoplamalar asosida yangi konstruksiya ishlab chiqish. TerDU ilmiy axborotnomasi, 5(3), 1–11.
MatchedFuzzy match, S = 1.00
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Kim S., Johnson M. (2008). Financial inclusion and small business development. The Lancet, 107, 588–966.
External source
11.
Kim S., Nguyen T., Silva R. (1998). Machine learning methods for credit scoring in developing countries. Journal of Chemical Education, 125, 26–973. https://doi.org/10.1021/acs.jchemed.1998.743026
External source
12.
Abdurahmonova S.M., Temirova Z.S., Abdullayev Z.T., va boshq. Kompressor qurilmasi uchun bazalt tolasi asosida yangi konstruksiya ishlab chiqish // FarPI ilmiy-texnika jurnali. – 2013. – №5. – B. 1–10. – DRI 20.1029/farpi/2013/v1_i5/89478287
MatchedExact by DRI
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Abdurahmonov S.J., Hasanov R.U. Shamol energiyasi manbalaridan foydalanib tishli uzatma energiya samaradorligini oshirish // TDTU ilmiy-uslubiy jurnali. – 2014. – №3. – B. 1–4.
MatchedFuzzy match, S = 1.00
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Silva R., Martin C. (2007). Soil salinity mapping using remote sensing data. IEEE Access, 166, 671–984.
External source
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Durdiyev J.A., Zaripov A.Z., Po'latova N.D., va boshq. Temir yo'l izi mustahkamlik ko'rsatkichlarini neyron tarmoqlar yordamida optimallashtirish // TDTU ilmiy-uslubiy jurnali. – 2012. – №4. – B. 5–9.
MatchedFuzzy match, S = 0.98
16.
O'zbekiston Respublikasi Prezidentining «2022–2026-yillarga mo'ljallangan Yangi O'zbekistonning taraqqiyot strategiyasi to'g'risida»gi PF-60-son Farmoni. – Toshkent, 2022.
External source
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Wang L. (1999). Soil salinity mapping using remote sensing data: evidence from panel data. Sustainability, 71, 435–975.
External source
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Brown A., Silva R., Garcia L. (2015). Deep residual learning for image recognition. Applied Linguistics, 66, 133–991. DOI: 10.1093/applin.2015.467148
External source
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Aliyev A.P. Elektr tarmogʼi ish rejimini eksperimental tadqiqot yordamida optimllashtirish // Texnika yulduzlari. – 2014. – №12. – B. 5–10.
MatchedFuzzy match, S = 1.00
20.
Müller K., Rossi F. (2001). A meta-analysis of active learning in STEM education revisited. World Development, 144, 415–911. DOI: 10.1016/j.worlddev.2001.356474
External source

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1–20 of 32

[1] 1.
Yusupova L.B., Zaripov A.Z., Ergashev H.I., va boshq. Geotermal energiya manbalaridan foydalanib tishli uzatma energiya samaradorligini oshirish // TDTU: fan, ta'lim va innovatsiya. – 2012. – №2. – B. 10–16. DRI: 20.1006/tdtufti/2012/v2_i2/51616884
MatchedExact by DRI→ Geotermal energiya manbalaridan foydalanib tishli uzatma energiya samaradorligini oshirish

[2] 2.
Shukurova R.N., Normatova U.M., Abdurahmonov S.J. Quyosh kollektori rejimini matematik modellashtirish yordamida optimallashtirish // TDTU: fan, ta'lim va innovatsiya. – 2012. – №2. – B. 1–9.
MatchedFuzzy match, S = 1.00→ Quyosh kollektori ish rejimini matematik modellashtirish yordamida optimallashtirish

[3] 3.
Chen Y., Wang L. (2011). Machine learning methods for credit scoring: evidence from panel data. IEEE Access, 39, 722–989. https://doi.org/10.1109/ACCESS.2011.626736
External source

[4] 4.
Po'latov, K. K. (2013). Оптимизация температурного режима солнечного коллектора емтодом математического моделирования. O'zMU xabarlari, 1–11. URL: https://nationaldri.uz/20.1002/71952824
MatchedExact by DRI

[5] 5.
Fayziyeva S.Z., Xamidova U.F. Nasos stansiyasi mustahkamlik ko'rsatkichlarini imitatsion modellashtirish yordamida optimallashtirish. – Toshkent: Innovatsiya, 2013. – 301 b.
MatchedFuzzy match, S = 1.00

[6] 6.
Abdurahmonova, S. M., Nazarova, Z. I., Ibragimova, Z. A., et al. (2014). Issiqlik almashtirgich uchun nanomateriallar asosida konstruksiya ishlab chiqish. FarPI ilmiy-texnika jurnali, 2(1), 1–8.
MatchedFuzzy match, S = 1.00

[7] 7.
Umarov B.Z., Mamatova O.M. Paxta tozalash mashinasi harorat rejimini genetik algoritm yordamida optimallashtirish // O’zDJTU ilmiy-uslubiy jurnali. – 2012. – №4. – B. 22–29.
MatchedFuzzy match, S = 1.00

[8] 8.
Haydarova, O'. M., & Zaripov, A. Z. (2014). Quyosh kollektori uchun mahalliy xomashyo asosida yangi konstruksiya ishlab chiqish. Texnika yulduzlari, 1–4. https://doi.org/10.52015/ty.2014.4.12.1
MatchedExact by DOI

[9] 9.
Umarov, B. Z., Moʼminova, Z. V., & Zaripova, Oʼ. A. (2013). Tishli uzatma uchun polimer qoplamalar asosida yangi konstruksiya ishlab chiqish. TerDU ilmiy axborotnomasi, 5(3), 1–11.
MatchedFuzzy match, S = 1.00

[10] 10.
Kim S., Johnson M. (2008). Financial inclusion and small business development. The Lancet, 107, 588–966.
External source

[11] 11.
Kim S., Nguyen T., Silva R. (1998). Machine learning methods for credit scoring in developing countries. Journal of Chemical Education, 125, 26–973. https://doi.org/10.1021/acs.jchemed.1998.743026
External source

[12] 12.
Abdurahmonova S.M., Temirova Z.S., Abdullayev Z.T., va boshq. Kompressor qurilmasi uchun bazalt tolasi asosida yangi konstruksiya ishlab chiqish // FarPI ilmiy-texnika jurnali. – 2013. – №5. – B. 1–10. – DRI 20.1029/farpi/2013/v1_i5/89478287
MatchedExact by DRI

[13] 13.
Abdurahmonov S.J., Hasanov R.U. Shamol energiyasi manbalaridan foydalanib tishli uzatma energiya samaradorligini oshirish // TDTU ilmiy-uslubiy jurnali. – 2014. – №3. – B. 1–4.
MatchedFuzzy match, S = 1.00

[14] 14.
Silva R., Martin C. (2007). Soil salinity mapping using remote sensing data. IEEE Access, 166, 671–984.
External source

[15] 15.
Durdiyev J.A., Zaripov A.Z., Po'latova N.D., va boshq. Temir yo'l izi mustahkamlik ko'rsatkichlarini neyron tarmoqlar yordamida optimallashtirish // TDTU ilmiy-uslubiy jurnali. – 2012. – №4. – B. 5–9.
MatchedFuzzy match, S = 0.98

[16] 16.
O'zbekiston Respublikasi Prezidentining «2022–2026-yillarga mo'ljallangan Yangi O'zbekistonning taraqqiyot strategiyasi to'g'risida»gi PF-60-son Farmoni. – Toshkent, 2022.
External source

[17] 17.
Wang L. (1999). Soil salinity mapping using remote sensing data: evidence from panel data. Sustainability, 71, 435–975.
External source

[18] 18.
Brown A., Silva R., Garcia L. (2015). Deep residual learning for image recognition. Applied Linguistics, 66, 133–991. DOI: 10.1093/applin.2015.467148
External source

[19] 19.
Aliyev A.P. Elektr tarmogʼi ish rejimini eksperimental tadqiqot yordamida optimllashtirish // Texnika yulduzlari. – 2014. – №12. – B. 5–10.
MatchedFuzzy match, S = 1.00

[20] 20.
Müller K., Rossi F. (2001). A meta-analysis of active learning in STEM education revisited. World Development, 144, 415–911. DOI: 10.1016/j.worlddev.2001.356474
External source