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Study of the effectiveness of ML algorithms in predicting the probability of crop disease occurrence
| dc.contributor.author | Vizniuk, Artem | |
| dc.contributor.author | Laktionov, Ivan | |
| dc.contributor.author | Diachenko, Grygorii | |
| dc.date.accessioned | 2024-06-24T10:00:53Z | |
| dc.date.available | 2024-06-24T10:00:53Z | |
| dc.date.issued | 2023 | |
| dc.identifier.citation | Vizniuk A. Study of the effectiveness of ML algorithms in predicting the probability of crop disease occurrence / Artem Vizniuk, Ivan Laktionov, Grygorii Diachenko // Проблеми використання інформаційних технологій в освіті, науці та промисловості : ХVIІІ міжнар. конф. (24 листопада 2023 р., м. Дніпро) : зб. наук. пр. – Дніпро : НТУ «ДП», 2023. – № 8. – C. 132-135. | uk_UA |
| dc.identifier.uri | http://ir.nmu.org.ua/handle/123456789/167216 | |
| dc.description.abstract | The aim of this research is to study the effectiveness of ML algorithms in predicting the probability of the corn disease «Fusarium Head Blight» in Dnipro region of Ukraine. Linear regression, feedforward neural networks and random forest models were considered for prediction. The random forest model obtained the best metric score on the testing set: R2=0.965, RMSE=3.44. Directions for further research were substantiated in the given subject area. | uk_UA |
| dc.language.iso | en | uk_UA |
| dc.subject | regression | uk_UA |
| dc.subject | ML | uk_UA |
| dc.subject | time series | uk_UA |
| dc.subject | disease prediction | uk_UA |
| dc.subject | crops | uk_UA |
| dc.subject | agriculture | uk_UA |
| dc.title | Study of the effectiveness of ML algorithms in predicting the probability of crop disease occurrence | uk_UA |
| dc.type | Article | uk_UA |
| dc.identifier.udk | 004.42 (8) | uk_UA |