Increasing the prediction accuracy of plant oil production processes through adjusting the parameters of machine learning models

Umidjon Ruziev, M.K. Shodiev, A.T. Rajabov

Кимёвий технология. Назорат ва бошқарув · 2026-yil

Annotatsiya

Vegetable oil production is characterized by high variability in output indicators due to nonlinear interactions between raw material parameters, equipment modes, and heat and mass transfer conditions. Existing approaches to applying machine learning in this field, as a rule, do not account for the impact of hyperparameter adjustments on forecasting quality across specific technological stages. The article presents a systematic methodology for adjusting model parameters (Ridge regression, SVR, GBM, LSTM) applied to three key tasks: predicting residual oil content in oil cake, color index during bleaching, and free fatty acid content during deodorization. In a set of 1000 observations, including technological, energy, and laboratory indicators, it is shown that adjusting hyperparameters improves forecast quality compared to basic model configurations; the best results were obtained for Gradient Boosting and LSTM.

Maqola ma’lumotlari
MualliflarUmidjon Ruziev, M.K. Shodiev, A.T. Rajabov
JurnalКимёвий технология. Назорат ва бошқарув
NashriyotТошкент давлат техника университети, «Ўзқурилишматериаллар» ДАК, «Ўзкимёсаноат» ДАК, «Совпластитал» ҚҚ, Ўзбекистон Интеллектуал мулк агентлиги
ISSN2181-1105, 1815-4840
Nashr sanasi2026-04-30
Jild2026
Son2
Betlar52-58
TilIngliz
Ilmiy sohaTexnika
DOI10.59048/2181-1105.1780
Indeksga qo‘shilgan2026-09-02

DOI: 10.59048/2181-1105.1780 · Maqolaning asl sahifasi

Ilmiy soha

Texnika

Iqtibos keltirish

APAUmidjon Ruziev, M.K. Shodiev, & A.T. Rajabov (2026). INCREASING THE PREDICTION ACCURACY OF PLANT OIL PRODUCTION PROCESSES THROUGH ADJUSTING THE PARAMETERS OF MACHINE LEARNING MODELS. Кимёвий технология. Назорат ва бошқарув, 2026(2), 52-58. https://doi.org/10.59048/2181-1105.1780
GOST (OAK)Umidjon Ruziev, M.K. Shodiev, A.T. Rajabov INCREASING THE PREDICTION ACCURACY OF PLANT OIL PRODUCTION PROCESSES THROUGH ADJUSTING THE PARAMETERS OF MACHINE LEARNING MODELS // Кимёвий технология. Назорат ва бошқарув. – 2026. – T. 2026, № 2. – P. 52-58. – DOI: 10.59048/2181-1105.1780.
MLAUmidjon Ruziev, M.K. Shodiev, and A.T. Rajabov. “INCREASING THE PREDICTION ACCURACY OF PLANT OIL PRODUCTION PROCESSES THROUGH ADJUSTING THE PARAMETERS OF MACHINE LEARNING MODELS.” Кимёвий технология. Назорат ва бошқарув, 2026(2), 52-58, 2026. https://doi.org/10.59048/2181-1105.1780
ChicagoUmidjon Ruziev, M.K. Shodiev, and A.T. Rajabov. “INCREASING THE PREDICTION ACCURACY OF PLANT OIL PRODUCTION PROCESSES THROUGH ADJUSTING THE PARAMETERS OF MACHINE LEARNING MODELS.” Кимёвий технология. Назорат ва бошқарув, 2026(2), 52-58 (2026). https://doi.org/10.59048/2181-1105.1780
HarvardUmidjon Ruziev, M.K. Shodiev, and A.T. Rajabov (2026) ‘INCREASING THE PREDICTION ACCURACY OF PLANT OIL PRODUCTION PROCESSES THROUGH ADJUSTING THE PARAMETERS OF MACHINE LEARNING MODELS’, Кимёвий технология. Назорат ва бошқарув, 2026(2), 52-58. https://doi.org/10.59048/2181-1105.1780
BibTeX
@article{umidjonruziev2026,
  title = {INCREASING THE PREDICTION ACCURACY OF PLANT OIL PRODUCTION PROCESSES THROUGH ADJUSTING THE PARAMETERS OF MACHINE LEARNING MODELS},
  author = {Umidjon Ruziev and M.K. Shodiev and A.T. Rajabov},
  journal = {Кимёвий технология. Назорат ва бошқарув},
  year = {2026},
  volume = {2026},
  number = {2},
  pages = {52-58},
  doi = {10.59048/2181-1105.1780},
  url = {https://doi.org/10.59048/2181-1105.1780}
}

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