Crop yield forecasting using neural networks trained on the basis of agrometeorological and agrochemical data

Описание

Тип публикации: доклад, тезисы доклада, статья из сборника материалов конференций

Конференция: International Scientific Conference on Biotechnology and Food Technology (BFT-2024); Saint Petersburg; Saint Petersburg

Год издания: 2024

Идентификатор DOI: 10.1051/bioconf/202413001011

Аннотация: <jats:p>In this study, a neural network model was developed and investigated for predicting crop yields based on data on weather conditions, the use of fertilizers and the content of basic nutrients in the soil (nitrogen, phosphorus and potassium). The research is based on the use of a multilayer perceptron architecture with Rely aПоказать полностьюctivation functions for hidden layers and linear activation for the output layer. The evaluation of the model quality was carried out using the mean square error (MSE), which was 0.5783 in the test sample, demonstrating high accuracy of predictions. Visualization of the results included analysis of scatter plots, residuals, histograms of residuals and comparison of distributions of actual and predicted values. The results obtained confirm the effectiveness of the proposed model for yield forecasting tasks, which makes it a valuable tool for optimizing agricultural production.</jats:p>

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Издание

Журнал: BIO WEB OF CONFERENCES

Выпуск журнала: 130

Номера страниц: 01011

Место издания: Les Ulis

Персоны

  • Degtyareva Ksenia
  • Tynchenko Vadim
  • Stepanov Nikita
  • Kalmykova Ekaterina
  • Makarevskaya Darya

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