Methods for intelligent modeling of industrial technological systems and optimization of real-time control strategies

Choriev, Urinjon

Techscience.uz - техника фанлари долзарб масалалри · 2025-yil

Annotatsiya

This article discusses methods for intelligent modeling of industrial technological systems and the optimization of real-time control strategies. Within the framework of the Industry 4.0 concept, the theoretical and practical foundations for integrating advanced technologies such as artificial intelligence, the Internet of Things (IoT), digital twins, neural networks, and Model Predictive Control (MPC) into industrial processes are presented. Special attention is paid to modeling complex chemical and petrochemical systems using both physics-based and data-driven approaches. The paper provides examples of implementing smoothing, forecasting, and optimization algorithms using Python code, graphs, and mathematical models. In addition, real-time optimization, the role of digital twins, and reinforcement learning technologies are analyzed as key stages in the transition of industry towards autonomous control systems.

Maqola ma’lumotlari
MualliflarChoriev, Urinjon
JurnalTechscience.uz - техника фанлари долзарб масалалри
NashriyotЖиззах политехника институти
ISSN3030-3702, 3030-3702
Nashr sanasi2025-12-27
Jild3
Son12
Betlar25-33
TilIngliz
Ilmiy sohaTexnika
DOI10.47390/ts-v3i12y2025n04
Indeksga qo‘shilgan2026-08-26

DOI: 10.47390/ts-v3i12y2025n04 · Maqolaning asl sahifasi

Kalit so‘zlar

artificial intelligence, IoT, Industry 4.0, intelligent modeling, real-time control, Model Predictive Control, neural networks, digital twin, chemical industry, oil and gas industry, forecasting, optimization, data-driven model., sun’iy intellekt, IoT, Industry 4.0, intellektual modellashtirish, real vaqt rejimidagi boshqaruv, Model Predictive Control, neyron tarmoqlar, raqamli egizak, kimyo sanoati, neft va gaz sanoati, bashoratlash, optimallashtirish, ma’lumotlarga asoslangan model.

Ilmiy soha

Texnika

Iqtibos keltirish

APAChoriev, Urinjon (2025). METHODS FOR INTELLIGENT MODELING OF INDUSTRIAL TECHNOLOGICAL SYSTEMS AND OPTIMIZATION OF REAL-TIME CONTROL STRATEGIES. Techscience.uz - техника фанлари долзарб масалалри, 3(12), 25-33. https://doi.org/10.47390/ts-v3i12y2025n04
GOST (OAK)Choriev, Urinjon METHODS FOR INTELLIGENT MODELING OF INDUSTRIAL TECHNOLOGICAL SYSTEMS AND OPTIMIZATION OF REAL-TIME CONTROL STRATEGIES // Techscience.uz - техника фанлари долзарб масалалри. – 2025. – T. 3, № 12. – P. 25-33. – DOI: 10.47390/ts-v3i12y2025n04.
MLAChoriev, Urinjon. “METHODS FOR INTELLIGENT MODELING OF INDUSTRIAL TECHNOLOGICAL SYSTEMS AND OPTIMIZATION OF REAL-TIME CONTROL STRATEGIES.” Techscience.uz - техника фанлари долзарб масалалри, 3(12), 25-33, 2025. https://doi.org/10.47390/ts-v3i12y2025n04
ChicagoChoriev, Urinjon. “METHODS FOR INTELLIGENT MODELING OF INDUSTRIAL TECHNOLOGICAL SYSTEMS AND OPTIMIZATION OF REAL-TIME CONTROL STRATEGIES.” Techscience.uz - техника фанлари долзарб масалалри, 3(12), 25-33 (2025). https://doi.org/10.47390/ts-v3i12y2025n04
HarvardChoriev, Urinjon (2025) ‘METHODS FOR INTELLIGENT MODELING OF INDUSTRIAL TECHNOLOGICAL SYSTEMS AND OPTIMIZATION OF REAL-TIME CONTROL STRATEGIES’, Techscience.uz - техника фанлари долзарб масалалри, 3(12), 25-33. https://doi.org/10.47390/ts-v3i12y2025n04
BibTeX
@article{chorievurinjon2025,
  title = {METHODS FOR INTELLIGENT MODELING OF INDUSTRIAL TECHNOLOGICAL SYSTEMS AND OPTIMIZATION OF REAL-TIME CONTROL STRATEGIES},
  author = {Choriev, Urinjon},
  journal = {Techscience.uz - техника фанлари долзарб масалалри},
  year = {2025},
  volume = {3},
  number = {12},
  pages = {25-33},
  doi = {10.47390/ts-v3i12y2025n04},
  url = {https://doi.org/10.47390/ts-v3i12y2025n04}
}

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