Analysis of the Effectiveness of Machine Learning Methods in Predicting Wheat Yields

Original title

Analysis of the Effectiveness of Machine Learning Methods in Predicting Wheat Yields

Russian translation

Анализ эффективности методов машинного обучения при прогнозировании урожайности пшеницы

Translation status: source

Evidence statuses

relation_layer

C — ecosystem

relation_confidence

3 — explicit

relevance_status

Included

body_status

Partial text or abstract

doi_status

Confirmed

access_status

Metadata only

expert_review

Included

verification_status

Metadata verified

Details

year

2024

type

Conference paper

venue

2024 4th International Conference on Technological Advancements in Computational Sciences (ICTACS)

DOI

10.1109/ictacs62700.2024.10840458

People

• P000791

Topics

• Biomass and yield
• Calibration and validation
• Forecasting and decision support
• Model comparison and ensembles
• System architecture

Sources

• ICTACS 2024 wheat-yield paper: Crossref DOI metadata
• Official ICTACS 2024 table of contents listing W001180
• OpenAlex abstract metadata for W001180
• Official IEEE public publisher record and abstract for W001180 ICTACS 2024 wheat-yield/AGROTOOL paper

External links

• https://doi.org/10.1109/ICTACS62700.2024.10840458
• https://ieeexplore.ieee.org/document/10840458/
• https://www.proceedings.com/content/078/078605webtoc.pdf
• https://www.researchgate.net/publication/388248956_Analysis_of_the_Effectiveness_of_Machine_Learning_Methods_in_Predicting_Wheat_Yields
• https://xplorestaging.ieee.org/ielx8/10840340/10840403/10840458.pdf?arnumber=10840458