Kompressor qurilmasi texnologik parametrlarini matematik modellashtirish yordamida optimallashtirish

Z. Mamatov; Qosimov Sh.A.; Sardor Shukurov; Jalilova Rayhona Anvar qizi; Baxromova Zarina G'ayrat qizi

doi:10.52045/tytm.2024.7.3.1

Maqola · 2024

Kompressor qurilmasi texnologik parametrlarini matematik modellashtirish yordamida optimallashtirish

Pasportni tahrirlash — nationaldri.uz

20.1031/tytm/2024/i3/43034008O'zbekcha

Pasport

nationaldri.uz registridagi pasport ko'zgusi. Tahrir faqat nationaldri.uz da amalga oshiriladi.

Mualliflar

Z. Mamatov ORCID 0000-0002-0028-837X (yangi oynada ochiladi)
TDTrU, Transport tizimlari fakulteti
Qosimov Sh.A.ORCID 0000-0002-0013-2412 (yangi oynada ochiladi)
Низомий номидаги Тошкент давлат педагогика университети
Sardor Shukurov ORCID 0000-0002-0028-7393 (yangi oynada ochiladi)
Toshkent davlat transport universiteti
Jalilova Rayhona Anvar qizi ORCID 0000-0002-0028-669X (yangi oynada ochiladi)
Тошкент давлат транспорт университети
Baxromova Zarina G'ayrat qiziprofil bog'lanmagan
Муҳаммад ал-Хоразмий номидаги Тошкент ахборот технологиялари университети

Annotatsiya

Ushbu maqolada «Kompressor qurilmasi texnologik parametrlarini matematik modellashtirish yordamida optimallashtirish» mavzusi tahlil qilingan. Tadqiqot davomida 98 nafar respondent ishtirokida tajriba-sinov ishlari o'tkazildi. Muallif tomonidan kompressor qurilmasi bo'yicha takliflar va tavsiyalar ishlab chiqilgan.

Kalit so'zlar

Bibliografik ma'lumotlar

DRI: 20.1031/tytm/2024/i3/43034008
Ish turi: Maqola
Jurnal: Temir yo'l transporti muammolariISSN 2181-0915
Jild va son: 3-son
Sahifalar: 1–10
Nashr sanasi: 9-iyun, 2024
Til: O'zbekcha
Tashqi DOI: 10.52045/tytm.2024.7.3.1 (yangi oynada ochiladi)
To'liq matn: Nashr sahifasida ochish (yangi oynada ochiladi)
Pasport ko'zgusi: 21.09.2026, 16:50 da sinxronlangan, versiya 1

Ko'rsatkichlar

Iqtiboslar

O'z-o'ziga iqtibossiz: 1

O'z-o'ziga iqtibossiz

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Manba bo'yicha statistika

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Manba bo'yicha statistika
Manba	Ko'rishlar	Yuklab olishlar
Jurnal sahifasijournal.milliykengash.com	0	0
Konferensiya to'plamiconference.milliykengash.com	0	0
DRI resolvernationaldri.uz orqali o'tishlar	3	—
Jami	3	0

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To'liq pasport (nationaldri.uz) (yangi oynada ochiladi)
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Adabiyotlar ro'yxati

Ish havola bergan manbalar va ularning registrdagi ishlar bilan moslashtirilishi.

Jami 16 ta yozuv6 ta moslandi0 ta moderatorda10 ta tashqi manba

1.
Egamberdiyev, S. A. (2022). Asinxron dvigatel ishonchliligini matematik modellashtirish bilan baholash (Navoiy viloyati misolida). Toshkent. – DRI 20.1027/diss/d2022/20868974
MoslandiDRI bo'yicha aniq→ Asinxron dvigatel ishonchliligini matematik modellashtirish bilan baholash (Navoiy viloyati misolida)
2.
Müller K., Martin C. (2006). Financial inclusion and small business development: a systematic review. Educational Psychology Review, 86, 94–948. https://doi.org/10.1007/s10648.2006.359075
Tashqi manba
3.
Kumar V., Müller K., Silva R. (2015). Machine learning methods for credit scoring. Agricultural Water Management, 9, 192–987.
Tashqi manba
4.
Toshmatov E.Sh. Nasos stansiysi ishonchliligini matematik modellashtirish bilan baholash // Texnika yulduzlari. – 2018. – №1. – B. 1–6. URL: https://nationaldri.uz/20.1006/ty/2018/i1/10328695
MoslandiDRI bo'yicha aniq
5.
Valiyev X.K., Aliyev Sh.A., G'afurova O.X., va boshq. Geotermal energiya manbalaridan foydalanib issiqlik almashtirgich energiya samaradorligini oshirish // TIQXMMI ilmiy-uslubiy jurnali. – 2013. – №5. – B. 1–13.
MoslandiTaxminiy moslik, S = 1,00
6.
Kumar V., Rossi F. (2001). Renewable energy transition in Central Asia: evidence from panel data. IEEE Access, 99, 381–922.
Tashqi manba
7.
Po'latov K.K. Оптимизация температурного режима солнечного коллектора методом математического моделриования // O'zMU xabarlari. – 2013. – B. 1–11. https://doi.org/10.52004/ozmux.2013.1.2.1
MoslandiDOI bo'yicha aniq
8.
Islomova L.E. Shamol energiyasi manbalaridan foydalanib nasos stansiyasi energiya samaradorligini oshirish. – Toshkent: Fan, 2017. – 244 b.
Tashqi manba
9.
Xolmatov, A. S., Norqulova, Y. I., Abdurahmonova, S. K., et al. (2017). Arterial gipertenziya bilan og'rigan homilador ayollarda fizioterapiya samaradorligi. Tibbiyot akademiyasi axborotnomasi, 3(1), 5–8. https://nationaldri.uz/20.1019/ttaa/2017/v3_i1/66382292
MoslandiDRI bo'yicha aniq
10.
Anderson R. (2009). Blockchain applications in public administration: evidence from panel data. Sustainability, 34, 577–989. https://doi.org/10.3390/su.2009.101711
Tashqi manba
11.
Schmidt P. (2016). Critical thinking assessment in university students: a systematic review. Journal of Economic Perspectives, 163, 749–981.
Tashqi manba
12.
Silva R., Martin C. (1998). A meta-analysis of active learning in STEM education: evidence from panel data. Sustainability, 157, 595–922.
Tashqi manba
13.
Wang L. Shamol generatori energiya sarfini genetik algoritm yordamida optimallashtirish. – Toshkent: Adabiyot uchqunlari, 2003. – 247 b.
Tashqi manba
14.
Chen Y., Nguyen T., Kim S. (2024). Machine learning methods for credit scoring. Energy Policy, 113, 533–972. DOI: 10.1016/j.enpol.2024.485867
Tashqi manba
15.
Jabborov B.D. Aralash turdagi kasr tartibli differensial tenglama uchun Trikomi masalasi // «Zamonaviy matematikaning dolzarb muammolari» mavzusidagi xalqaro ilmiy-amaliy konferensiya materiallari. – Toshkent, 2015. – B. 5–8. DRI: 20.1002/ozmuconf2015/2015/93184166
MoslandiDRI bo'yicha aniq
16.
Schmidt P. (2023). Deep residual learning for image recognition: evidence from panel data. World Development, 10, 379–951. https://doi.org/10.1016/j.worlddev.2023.186209
Tashqi manba

Iqtibos beruvchi ishlar

Registrdagi shu ishga havola bergan ishlar, yangilari birinchi.

Temir yo'l izi harorat rejimini genetik algoritm yordamida optimallashtirish (Andijon viloyati misolida)
Mualliflar: Mansurova Rayhona Ilhomovna, Ismoilov Odil, Davletov RustamTDTU ilmiy-uslubiy jurnali
DRI20.1006/tdtuilm/2024/v16_i4/33416140 nationaldri.uz da ochishMaqola2ko'rish0yuklab olish
Yil2024
Iqtiboslar0

[1] 1.
Egamberdiyev, S. A. (2022). Asinxron dvigatel ishonchliligini matematik modellashtirish bilan baholash (Navoiy viloyati misolida). Toshkent. – DRI 20.1027/diss/d2022/20868974
MoslandiDRI bo'yicha aniq→ Asinxron dvigatel ishonchliligini matematik modellashtirish bilan baholash (Navoiy viloyati misolida)

[2] 2.
Müller K., Martin C. (2006). Financial inclusion and small business development: a systematic review. Educational Psychology Review, 86, 94–948. https://doi.org/10.1007/s10648.2006.359075
Tashqi manba

[3] 3.
Kumar V., Müller K., Silva R. (2015). Machine learning methods for credit scoring. Agricultural Water Management, 9, 192–987.
Tashqi manba

[4] 4.
Toshmatov E.Sh. Nasos stansiysi ishonchliligini matematik modellashtirish bilan baholash // Texnika yulduzlari. – 2018. – №1. – B. 1–6. URL: https://nationaldri.uz/20.1006/ty/2018/i1/10328695
MoslandiDRI bo'yicha aniq

[5] 5.
Valiyev X.K., Aliyev Sh.A., G'afurova O.X., va boshq. Geotermal energiya manbalaridan foydalanib issiqlik almashtirgich energiya samaradorligini oshirish // TIQXMMI ilmiy-uslubiy jurnali. – 2013. – №5. – B. 1–13.
MoslandiTaxminiy moslik, S = 1,00

[6] 6.
Kumar V., Rossi F. (2001). Renewable energy transition in Central Asia: evidence from panel data. IEEE Access, 99, 381–922.
Tashqi manba

[7] 7.
Po'latov K.K. Оптимизация температурного режима солнечного коллектора методом математического моделриования // O'zMU xabarlari. – 2013. – B. 1–11. https://doi.org/10.52004/ozmux.2013.1.2.1
MoslandiDOI bo'yicha aniq

[8] 8.
Islomova L.E. Shamol energiyasi manbalaridan foydalanib nasos stansiyasi energiya samaradorligini oshirish. – Toshkent: Fan, 2017. – 244 b.
Tashqi manba

[9] 9.
Xolmatov, A. S., Norqulova, Y. I., Abdurahmonova, S. K., et al. (2017). Arterial gipertenziya bilan og'rigan homilador ayollarda fizioterapiya samaradorligi. Tibbiyot akademiyasi axborotnomasi, 3(1), 5–8. https://nationaldri.uz/20.1019/ttaa/2017/v3_i1/66382292
MoslandiDRI bo'yicha aniq

[10] 10.
Anderson R. (2009). Blockchain applications in public administration: evidence from panel data. Sustainability, 34, 577–989. https://doi.org/10.3390/su.2009.101711
Tashqi manba

[11] 11.
Schmidt P. (2016). Critical thinking assessment in university students: a systematic review. Journal of Economic Perspectives, 163, 749–981.
Tashqi manba

[12] 12.
Silva R., Martin C. (1998). A meta-analysis of active learning in STEM education: evidence from panel data. Sustainability, 157, 595–922.
Tashqi manba

[13] 13.
Wang L. Shamol generatori energiya sarfini genetik algoritm yordamida optimallashtirish. – Toshkent: Adabiyot uchqunlari, 2003. – 247 b.
Tashqi manba

[14] 14.
Chen Y., Nguyen T., Kim S. (2024). Machine learning methods for credit scoring. Energy Policy, 113, 533–972. DOI: 10.1016/j.enpol.2024.485867
Tashqi manba

[15] 15.
Jabborov B.D. Aralash turdagi kasr tartibli differensial tenglama uchun Trikomi masalasi // «Zamonaviy matematikaning dolzarb muammolari» mavzusidagi xalqaro ilmiy-amaliy konferensiya materiallari. – Toshkent, 2015. – B. 5–8. DRI: 20.1002/ozmuconf2015/2015/93184166
MoslandiDRI bo'yicha aniq

[16] 16.
Schmidt P. (2023). Deep residual learning for image recognition: evidence from panel data. World Development, 10, 379–951. https://doi.org/10.1016/j.worlddev.2023.186209
Tashqi manba

month	Ko'rishlar	Yuklab olishlar
iyn 2026	1	0
iyl 2026	1	0
sen 2026	1	0

month	Ko'rishlar	Yuklab olishlar
iyn 2026	1	0
iyl 2026	1	0
sen 2026	1	0