An integrated model for ai-based forecasting of technical service demand and optimal resource allocation in agro-industrial complexes

Usarkulova , Feruza

Techscience.uz - техника фанлари долзарб масалалри · 2026-yil

Annotatsiya

This paper proposes an integrated decision model for forecasting technical-service demand and allocating limited maintenance resources in agro-industrial complexes. The forecasting layer represents daily, intermittent service requests by zone and service category through a Poisson gradient-boosting model with calendar, weather, fleet, workload and lagged-demand features. A split-conformal procedure converts point predictions into empirical uncertainty margins. The prescriptive layer is formulated as a mixed-integer linear program that assigns team-days and service jobs subject to skill compatibility, regular and overtime capacity, spare-parts availability and shortage penalties. A reproducible controlled experiment with 21,600 zone-category-day observations is used to test the computational procedure. The HGB–Poisson model reduces MAE and RMSE relative to seasonal-naive and Croston–SBA benchmarks. In a calendar-defined 14-day workload window, budgeted-robust AI planning improves realized service continuity compared with a historical seasonal plan. The results support a rolling-horizon software architecture in which forecasts and allocation decisions are updated from completed work orders.

Maqola ma’lumotlari
MualliflarUsarkulova , Feruza
JurnalTechscience.uz - техника фанлари долзарб масалалри
NashriyotЖиззах политехника институти
ISSN3030-3702, 3030-3702
Nashr sanasi2026-09-16
Jild4
Son9
Betlar34-43
TilIngliz
Ilmiy sohaTexnika
DOI10.47390/ts-v4i9y2026n05
Indeksga qo‘shilgan2026-09-17

DOI: 10.47390/ts-v4i9y2026n05 · Maqolaning asl sahifasi

Kalit so‘zlar

agro-industrial complex; technical service; intermittent demand; artificial intelligence; mathematical modeling; mixed-integer programming; robust allocation; software complex., agrosanoat majmuasi; texnik servis; uzlukli talab; sun’iy intellekt; matematik modellashtirish; aralash butun sonli dasturlash; robust taqsimlash; dasturlar majmui.

Ilmiy soha

Texnika

Iqtibos keltirish

APAUsarkulova , Feruza (2026). AN INTEGRATED MODEL FOR AI-BASED FORECASTING OF TECHNICAL SERVICE DEMAND AND OPTIMAL RESOURCE ALLOCATION IN AGRO-INDUSTRIAL COMPLEXES. Techscience.uz - техника фанлари долзарб масалалри, 4(9), 34-43. https://doi.org/10.47390/ts-v4i9y2026n05
GOST (OAK)Usarkulova , Feruza AN INTEGRATED MODEL FOR AI-BASED FORECASTING OF TECHNICAL SERVICE DEMAND AND OPTIMAL RESOURCE ALLOCATION IN AGRO-INDUSTRIAL COMPLEXES // Techscience.uz - техника фанлари долзарб масалалри. – 2026. – T. 4, № 9. – P. 34-43. – DOI: 10.47390/ts-v4i9y2026n05.
MLAUsarkulova , Feruza. “AN INTEGRATED MODEL FOR AI-BASED FORECASTING OF TECHNICAL SERVICE DEMAND AND OPTIMAL RESOURCE ALLOCATION IN AGRO-INDUSTRIAL COMPLEXES.” Techscience.uz - техника фанлари долзарб масалалри, 4(9), 34-43, 2026. https://doi.org/10.47390/ts-v4i9y2026n05
ChicagoUsarkulova , Feruza. “AN INTEGRATED MODEL FOR AI-BASED FORECASTING OF TECHNICAL SERVICE DEMAND AND OPTIMAL RESOURCE ALLOCATION IN AGRO-INDUSTRIAL COMPLEXES.” Techscience.uz - техника фанлари долзарб масалалри, 4(9), 34-43 (2026). https://doi.org/10.47390/ts-v4i9y2026n05
HarvardUsarkulova , Feruza (2026) ‘AN INTEGRATED MODEL FOR AI-BASED FORECASTING OF TECHNICAL SERVICE DEMAND AND OPTIMAL RESOURCE ALLOCATION IN AGRO-INDUSTRIAL COMPLEXES’, Techscience.uz - техника фанлари долзарб масалалри, 4(9), 34-43. https://doi.org/10.47390/ts-v4i9y2026n05
BibTeX
@article{usarkulovaferuza2026,
  title = {AN INTEGRATED MODEL FOR AI-BASED FORECASTING OF TECHNICAL SERVICE DEMAND AND OPTIMAL RESOURCE ALLOCATION IN AGRO-INDUSTRIAL COMPLEXES},
  author = {Usarkulova , Feruza},
  journal = {Techscience.uz - техника фанлари долзарб масалалри},
  year = {2026},
  volume = {4},
  number = {9},
  pages = {34-43},
  doi = {10.47390/ts-v4i9y2026n05},
  url = {https://doi.org/10.47390/ts-v4i9y2026n05}
}

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