Machine learning-assisted prediction of fire-retardant and preservative performance of chemically modified wood: an eco-friendly approach

Usmanova , Maftunakhon

Муҳандислик ва Иқтисодиёт · 2026-yil

Annotatsiya

Wood protection currently relies on agents that are effective but environmentally problematic, while the searchfor bio-based alternatives is hindered by the vast formulation design space. A critical review of eco-friendly fire-retardantand preservative chemistries for wood is integrated with a proposed experimental design and a supervised machine-learningframework for predicting performance outcomes. Three candidate systems are considered: phytic acid with silicananosol; condensed tannin fixed with hexamine and boric acid; and chitosan combined with caffeine. Performance rangesreported in the literature are synthesised, an experimental factor structure suitable for regression modelling is specified,and a modelling protocol based on regularised regression, tree ensembles, and a compact neural network, incorporatingnested cross-validation and SHAP-based attribution, is proposed. At this stage, no experimental data have been collectedby the author; all quantitative values presented are derived from published studies and are cited accordingly.

Maqola ma’lumotlari
MualliflarUsmanova , Maftunakhon
JurnalМуҳандислик ва Иқтисодиёт
NashriyotПлеханов номидаги Россия иқтисодиёти университетининг Тошкент шаҳридаги филиали
ISSN3060-463X, 3060-463X
Nashr sanasi2026-08-01
Jild4
Son8
Betlar52-59
TilIngliz
Ilmiy sohaTexnika
Indeksga qo‘shilgan2026-09-06

Maqolaning asl sahifasi

Kalit so‘zlar

wood modification; phytic acid; condensed tannin; chitosan; flame retardancy; decay resistance; machine learning; QSPR; SHAP.

Ilmiy soha

Texnika

Iqtibos keltirish

APAUsmanova , Maftunakhon (2026). MACHINE LEARNING-ASSISTED PREDICTION OF FIRE-RETARDANT AND PRESERVATIVE PERFORMANCE OF CHEMICALLY MODIFIED WOOD: AN ECO-FRIENDLY APPROACH. Муҳандислик ва Иқтисодиёт, 4(8), 52-59. https://muhandislik-iqtisodiyot.uz/index.php/journal/article/view/4060
GOST (OAK)Usmanova , Maftunakhon MACHINE LEARNING-ASSISTED PREDICTION OF FIRE-RETARDANT AND PRESERVATIVE PERFORMANCE OF CHEMICALLY MODIFIED WOOD: AN ECO-FRIENDLY APPROACH // Муҳандислик ва Иқтисодиёт. – 2026. – T. 4, № 8. – P. 52-59.
MLAUsmanova , Maftunakhon. “MACHINE LEARNING-ASSISTED PREDICTION OF FIRE-RETARDANT AND PRESERVATIVE PERFORMANCE OF CHEMICALLY MODIFIED WOOD: AN ECO-FRIENDLY APPROACH.” Муҳандислик ва Иқтисодиёт, 4(8), 52-59, 2026. https://muhandislik-iqtisodiyot.uz/index.php/journal/article/view/4060
ChicagoUsmanova , Maftunakhon. “MACHINE LEARNING-ASSISTED PREDICTION OF FIRE-RETARDANT AND PRESERVATIVE PERFORMANCE OF CHEMICALLY MODIFIED WOOD: AN ECO-FRIENDLY APPROACH.” Муҳандислик ва Иқтисодиёт, 4(8), 52-59 (2026). https://muhandislik-iqtisodiyot.uz/index.php/journal/article/view/4060
HarvardUsmanova , Maftunakhon (2026) ‘MACHINE LEARNING-ASSISTED PREDICTION OF FIRE-RETARDANT AND PRESERVATIVE PERFORMANCE OF CHEMICALLY MODIFIED WOOD: AN ECO-FRIENDLY APPROACH’, Муҳандислик ва Иқтисодиёт, 4(8), 52-59. https://muhandislik-iqtisodiyot.uz/index.php/journal/article/view/4060
BibTeX
@article{usmanovamaftunakhon2026,
  title = {MACHINE LEARNING-ASSISTED PREDICTION OF FIRE-RETARDANT AND PRESERVATIVE PERFORMANCE OF CHEMICALLY MODIFIED WOOD: AN ECO-FRIENDLY APPROACH},
  author = {Usmanova , Maftunakhon},
  journal = {Муҳандислик ва Иқтисодиёт},
  year = {2026},
  volume = {4},
  number = {8},
  pages = {52-59},
  url = {https://muhandislik-iqtisodiyot.uz/index.php/journal/article/view/4060}
}

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