SUT MAHSULOTLARINI SAQLASHNI NOQALIK MANTIQ ASOSHIDA OPTIMALLASHTIRISH. VA KATTA MA'LUMOTLARNI TAHLILI
Kalit so‘zlar:
Dairy product storage, Fuzzy logic, Big data, Artificial intelligence, Process optimization, Food safetyAbstrak
Samarali saqlash tizimlari sifati, xavfsizligi va xavfsizligini ta'minlashda hal qiluvchi rol o'ynaydi
sut mahsulotlarining saqlash muddati. Ushbu tadqiqot sut mahsulotlarini optimallashtirish uchun yangi yondashuvni taqdim etadi
loyqa mantiqqa asoslangan algoritmlar va katta ma'lumotlarni tahlil qilish orqali saqlash jarayonini boshqarish tizimlari.
Noaniq mantiq harorat, namlik va kabi noaniq omillarni boshqarish uchun qo'llaniladi
an'anaviy nazorat usullari uchun qiyinchiliklar tug'diradigan mikrobiologik faollik. Taklif etilgan
tizim sensor ma'lumotlariga (harorat, pH, namlik) asoslangan loyqa mantiq qoidalarini qo'llaydi.
real vaqt rejimida sovutish, ventilyatsiya va sterilizatsiya jarayonlarini nazorat qilish. Katta ma'lumotlarni tahlil qilish jarayonlari
buzilish xavfini bashorat qilish va saqlashni dinamik ravishda optimallashtirish uchun tarixiy va real vaqtda ma'lumotlar
sharoitlar. Vaqt seriyalarini prognozlash va klasterlash kabi mashinalarni o'rganish modellari yaxshilanadi
qaror qabul qilishning aniqligi. Simulyatsiya natijalari energiyaning potentsial 15% qisqarishini ko'rsatadi
iste'mol va mahsulotning saqlash muddatini 20% ga oshirish. Bu ish sun'iy intellektni bog'laydi va
oziq-ovqat xavfsizligi uchun katta ma'lumotlar, ovqatlanish dasturlari uchun xavfsiz sut ta'minotini ta'minlashga hissa qo'shish,
ayniqsa sog'liqni saqlash sohasida.
References
Zadeh, L. A. (1965). Fuzzy sets. Information and Control, 8(3), 338–353. https://doi.org/10.1016/S0019-9958(65)90241-X
Mendel, J. M. (2001). Uncertain rule-based fuzzy logic systems: Introduction and new directions. PrenticeHall PTR.
Yager, R. R. (1980). Fuzzy decision making including unequal objectives. Fuzzy Sets and Systems, 4(1), 87–95.
Jain, A., & Dubey, S. (2016). Design and implementation of fuzzy logic controller for refrigeration system. International Journal of Engineering Research & Technology (IJERT), 5(10), 278–281.
Beghi, A., Cecchinato, L., Rampazzo, M., & Scarpa, F. (2014). Model predictive control of a domestic refrigerator. Applied Thermal Engineering, 70(1), 896–904.
Rutkowski, L. (2004). Flexible neuro-fuzzy systems: Structures, learning and performance evaluation. Springer-Verlag.
Li, S., Xu, L. D., & Zhao, S. (2015). The internet of things: A survey. Information Systems Frontiers, 17(2), 243–259. https://doi.org/10.1007/s10796-014-9492-7
Raxmonqulov, U. I. (2021). Oziq-ovqat mahsulotlarini saqlashda mikroiqlim parametrlarini boshqarishning zamonaviy yondashuvlari. Texnika fanlari axborotnomasi, 3(4), 45–50.
Xudayberganov, I. G. (2020). Sovitilgan omborxonalarda harorat va havo aylanishining matematik modeli. O‘zbekiston fanlari akademiyasi axborotlari. Texnika fanlari seriyasi, (2), 66–72.
Sattarov, A. A. (2022). Sovitkich tizimlarida avtomatik boshqaruvning samarali modellari. Fan va innovatsiya, 1(1), 88–95.
Xolmatova, F. T. (2023). Monitoring tizimlari yordamida sut mahsulotlarini saqlashni optimallashtirish. Amaliy ilm-fan yutuqlari, 2(3), 101–106.
Rashid, M. M., Hasan, M. M., & Uddin, M. S. (2018). IoT based smart refrigeration system for perishable food monitoring. Journal of Computer and Communications, 6(9), 15–21.
Gallo, M., Romano, E., & Santillo, L. C. (2017). A fuzzy decision support system for warehouse management integrating big data analytics. Computers & Industrial Engineering, 109, 174–186. https://doi.org/10.1016/j.cie.2017.04.023
Zhou, J., Lin, J., & Wang, Y. (2020). Predictive control of smart cold chain logistics system based on environmental sensor data. Sensors, 20(11), 3203. https://doi.org/10.3390/s20113203
Jo‘rayev, D. T. (2022). MATLAB muhitida fuzzy algoritm asosida sut mahsulotlarini saqlash tizimini modellashtirish. O‘zbekistonda innovatsion texnologiyalar, 4(1), 77–82.
A. K. Pal, "IoT-based real-time data acquisition and control for industrial applications," IEEE Internet of Things Journal, vol. 7, no. 4, pp. 2956-2964, 2020. DOI: 10.1109/JIOT.2019.2956789.
L. A. Zadeh, "Fuzzy sets," Information and Control, vol. 8, no. 3, pp. 338-353, 1965. DOI: 10.1016/S0019-9958(65)90241-X.
H. Ying, "Fuzzy control and modeling: Analytical foundations and applications," IEEE Press Series on Biomedical Engineering, 2000. DOI: 10.1109/9780470544730.
S. Hochreiter and J. Schmidhuber, "Long short-term memory," Neural Computation, vol. 9, no. 8, pp. 1735-1780, 1997. DOI: 10.1162/neco.1997.9.8.1735.
J. MacQueen, "Some methods for classification and analysis of multivariate observations," in Proceedings of the Fifth Berkeley Symposium on Mathematical Statistics and Probability, vol. 1, pp. 281-297, 1967. [Online]. Available: https://projecteuclid.org/euclid.bsmsp/1200512992.
D. W. Hosmer, S. Lemeshow, and R. X. Sturdivant, Applied Logistic Regression, 3rd ed. Wiley, 2013. ISBN: 978-0470582473.
J. Nocedal and S. J. Wright, Numerical Optimization, 2nd ed. Springer, 2006. ISBN: 978-0387303031.
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